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BMR Calculator

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BMR Calculator — Compare 3 Equations
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Your current body weight

Your height in centimetres

Your age in years

If known, enables the Katch-McArdle equation

Calorie and macronutrient estimates are based on peer-reviewed metabolic formulas and population averages. Your actual energy needs may differ due to genetics, medical conditions, medications, and other factors. These results do not constitute nutritional or medical advice. Consult a registered dietitian or healthcare professional for personalised guidance.

The BMR Calculator estimates your BMR using three peer-reviewed equations — Mifflin-St Jeor, Harris-Benedict, and Katch-McArdle — and displays the results side by side for comparison.

Basal Metabolic Rate is not the number of calories you need to survive, and confusing BMR with a minimum safe intake is one of the most common and potentially harmful misunderstandings in nutrition. BMR estimates the energy your body uses at absolute rest — lying still in a temperature-controlled room after an overnight fast — just to keep your heart beating, your lungs breathing, and your cells repairing. It does not account for digestion, standing up, walking to the kitchen, or any other activity. Actual daily energy needs are substantially higher, typically 1.2 to 1.9 times BMR depending on lifestyle. Anyone using their BMR figure as a calorie target is almost certainly eating well below their real energy requirements.

Understanding the Calculation

This calculator implements three equations that each take a different approach to predicting resting metabolism. Two of them — Mifflin-St Jeor and Harris-Benedict — use weight, height, age, and sex. The third — Katch-McArdle — ignores all demographic variables and relies entirely on LBM (lean body mass).

The Mifflin-St Jeor equation (1990) applies these coefficients:

  • Males: (10 × weight in kg) + (6.25 × height in cm) − (5 × age in years) + 5
  • Females: (10 × weight in kg) + (6.25 × height in cm) − (5 × age in years) − 161

The sex-specific constants (+5 for males, −161 for females) reflect the average difference in lean mass between sexes at equivalent body weights.

The Harris-Benedict equation has the longest history of any metabolic prediction formula. James Arthur Harris and Francis Gano Benedict published the original in 1919, derived from calorimetry data on 239 subjects. By the 1980s, researchers recognised that changes in average body composition and improved statistical methods warranted a revision. Roza and Shizgal published the updated version in 1984 in the American Journal of Clinical Nutrition. The revised equation uses different coefficients for each variable and tends to produce slightly higher estimates than Mifflin-St Jeor, typically by 50–100 kcal/day.

The Katch-McArdle equation (1983) takes a fundamentally different approach: BMR = 370 + (21.6 × LBM in kg). Because it uses lean body mass rather than total weight, it is sex-neutral and age-neutral by design. The logic is straightforward — metabolic rate correlates more closely with muscle and organ mass than with total body weight, so measuring the metabolically active compartment directly should yield a better prediction. The trade-off is that it requires an accurate body fat percentage. If you do not have a recent measurement, tools such as the body fat estimation method using Navy tape or skinfold calipers can provide an approximate figure.

Comparing the Formulas

For an average-build individual, the three equations tend to agree within 50–100 kcal. The divergence grows at the extremes of body composition and age, which is where formula selection starts to matter.

ScenarioMifflin-St JeorHarris-BenedictKatch-McArdle
30M, 80 kg, 178 cm, no body fat data1,768 kcal1,844 kcalNot available
32F, 62 kg, 168 cm, 22% body fat1,349 kcal1,403 kcal1,415 kcal

In the first row, the 76 kcal gap between formulas is small enough that either equation provides a reasonable estimate. In the second row, all three formulas cluster within 66 kcal — a particularly tight grouping that reflects the moderate body composition of the subject. For individuals with very low or very high body fat, the gap between weight-based formulas (Mifflin-St Jeor and Harris-Benedict) and the lean-mass-based Katch-McArdle tends to widen, making the third formula more valuable.

The average of all available formulas — shown in the calculator results — provides a practical single estimate that smooths out the individual biases of each equation.

What This Tool Cannot Do

BMR calculators estimate resting metabolism using regression equations derived from population studies. Several important limitations apply.

No population-based formula accounts for individual genetic variation in metabolic rate. Research suggests that BMR can vary by 5–8% between individuals of the same age, sex, height, and weight due to differences in organ size, thyroid function, and mitochondrial efficiency. Factors such as sleep quality and metabolic rate are closely linked — chronic sleep restriction has been shown to reduce resting metabolic rate by 2–5%, an effect none of these equations can capture. The equations predict the average for a given set of inputs, not the specific value for any one person.

These formulas also cannot detect metabolic adaptation. During prolonged calorie restriction, the body downregulates metabolic rate beyond what changes in body weight would predict. A person who has been dieting for several months may have a BMR 10–15% lower than what any equation estimates. Conversely, after a period of overfeeding, metabolic rate may be temporarily elevated. The calculator reflects static inputs, not metabolic history.

Finally, RMR (Resting Metabolic Rate) is not identical to BMR, though the terms are often used interchangeably. RMR is measured under slightly less restrictive conditions — the subject is rested but not necessarily fasted for 12 hours in a thermoneutral room. RMR typically runs 3–10% higher than BMR. The equations in this calculator estimate BMR specifically, following the original study protocols.

Tips for Better Results

Accurate inputs produce better estimates, and a few practical considerations improve the quality of the data fed into these equations.

  • Weigh yourself in the morning after using the bathroom and before eating or drinking. Evening weight can be 1–2 kg higher due to food, water, and fluid retention.
  • Measure height carefully. A 2 cm error in height changes the Mifflin-St Jeor estimate by approximately 12.5 kcal — small on its own, but errors compound when combined with other input inaccuracies.
  • Use body fat percentage if available. Even an approximate measurement enables the Katch-McArdle equation and provides a useful third data point for cross-referencing.
  • Recalculate periodically. A 5 kg weight change, a birthday that crosses a decade boundary, or a significant shift in body composition all warrant a fresh estimate.

For most nutrition planning purposes, BMR alone is not the useful number — it is the starting point for a total daily energy expenditure estimate that accounts for activity, or for splitting calories into a macronutrient split calculator once a daily target is established.

From BMR to a Practical Calorie Target

BMR represents the floor of your energy expenditure — the cost of simply existing. In exercise science, this resting energy cost is standardised as 1 MET; browsing the MET values where 1 MET equals your resting metabolic rate table shows how different activities scale relative to this baseline. Every additional activity layered on top raises total energy needs. To translate BMR into something actionable, multiply it by an activity factor to estimate TDEE, then adjust that TDEE based on goals: a moderate deficit for fat loss, maintenance for weight stability, or a surplus for muscle gain.

The distinction matters because people who skip the activity multiplier and eat at or near their BMR are almost certainly in a steep deficit that risks muscle loss, nutrient deficiency, and metabolic downregulation. A safe and effective deficit typically subtracts 300–500 kcal from TDEE — not from BMR. For guidance on structuring a deficit, the calorie deficit planning tool calculates appropriate targets while respecting minimum calorie floors. Understanding where your body mass index assessment falls can also provide useful context alongside BMR when evaluating overall body composition.

Basal Metabolic Rate

The minimum energy expenditure required to sustain vital organ function in a completely rested, fasted, thermoneutral state. BMR typically accounts for 60–75% of total daily energy expenditure in sedentary individuals and decreases with age, weight loss, and reduced lean body mass.

Lean Body Mass

Total body weight minus fat mass. Lean body mass includes muscle, bone, organs, water, and connective tissue — essentially everything that is not stored body fat. It is the sole input to the Katch-McArdle equation because metabolic rate correlates more strongly with lean tissue than with total weight.

Resting Metabolic Rate

A measurement of energy expenditure taken under resting but less strictly controlled conditions than BMR. RMR is easier to measure clinically because it does not require an overnight stay in a thermoneutral chamber. It typically exceeds BMR by 3–10% and is sometimes used interchangeably with BMR in informal contexts, though the two are technically distinct.

Metabolic Adaptation

A reduction in metabolic rate that exceeds what body weight changes alone would predict, occurring during sustained calorie restriction. Also called adaptive thermogenesis, this phenomenon means that someone who has been dieting for months may burn fewer calories at rest than an equation would estimate for their current weight. Metabolic adaptation is one reason that calculated BMR values become less accurate over time during prolonged energy restriction.

Bar chart comparing Mifflin-St Jeor, Harris-Benedict, and Katch-McArdle basal metabolic rate estimates.

Worked Examples

Three-Formula Comparison Without Body Fat

Context

A 30-year-old male weighs 80 kg and stands 178 cm tall. He does not know his body fat percentage, so only Mifflin-St Jeor and Harris-Benedict can produce estimates. This scenario is the most common use case — someone who wants a BMR baseline without access to body composition data.

Calculation

Mifflin-St Jeor: (10 × 80) + (6.25 × 178) − (5 × 30) + 5 = 800 + 1,112.5 − 150 + 5 = 1,768 kcal/day. Harris-Benedict (Revised): (13.397 × 80) + (4.799 × 178) − (5.677 × 30) + 88.362 = 1,071.8 + 854.2 − 170.3 + 88.4 = 1,844 kcal/day. Katch-McArdle: not available (no body fat data). Average of available formulas: (1,768 + 1,844) ÷ 2 = 1,806 kcal/day.

Interpretation

The two formulas differ by 76 kcal/day, with Harris-Benedict producing the higher estimate. This gap is typical — Harris-Benedict tends to run slightly above Mifflin-St Jeor for males in this age and weight range. A 76 kcal difference is well within the expected prediction error of both equations and amounts to roughly one medium banana per day.

Takeaway

When only two formulas are available, the average (1,806 kcal) provides a reasonable middle estimate. To enable the third formula and get a more individualised result, consider using a body composition tool to obtain an approximate body fat percentage.

All Three Formulas With Body Fat Percentage

Context

A 32-year-old female weighs 62 kg, stands 168 cm tall, and has measured her body fat at 22% using skinfold calipers. With body fat data available, all three equations — including Katch-McArdle — can be compared side by side.

Calculation

Mifflin-St Jeor: (10 × 62) + (6.25 × 168) − (5 × 32) − 161 = 620 + 1,050 − 160 − 161 = 1,349 kcal/day. Harris-Benedict (Revised): (9.247 × 62) + (3.098 × 168) − (4.330 × 32) + 447.593 = 573.3 + 520.5 − 138.6 + 447.6 = 1,403 kcal/day. Lean body mass: 62 × (1 − 0.22) = 48.36 kg. Katch-McArdle: 370 + (21.6 × 48.36) = 370 + 1,044.6 = 1,415 kcal/day. Average of all three: (1,349 + 1,403 + 1,415) ÷ 3 = 1,389 kcal/day.

Interpretation

All three formulas cluster within a 66 kcal range (1,349 to 1,415 kcal). Katch-McArdle produces the highest estimate here because 22% body fat corresponds to a lean, active body composition in females, meaning the lean-mass-based formula gives credit for the relatively high proportion of metabolically active tissue. The tight agreement across all three formulas suggests high confidence in an estimated BMR near 1,389 kcal/day.

Takeaway

Having all three formulas agree closely is a strong signal that the estimate is reliable. If the three results had diverged significantly — say by 150+ kcal — it would suggest reviewing the input data, particularly the body fat percentage measurement. Use the three-formula average as the most robust single estimate when all inputs are available.

Frequently Asked Questions

Frequently Asked Questions

Is BMR the same as the minimum calories I need?
No — this is one of the most persistent myths in nutrition. BMR estimates the energy required to sustain organ function at complete rest, but it does not represent a safe minimum calorie intake. Actual daily energy needs are significantly higher than BMR because the body also expends energy on digestion, movement, and all physical activity. The total daily energy expenditure estimate accounts for these additional demands and provides a more practical baseline for nutrition planning.
Which BMR equation is most accurate?
For the general population, Mifflin-St Jeor (1990) has been shown in multiple validation studies to produce the smallest average prediction error. The American Dietetic Association endorsed it as the preferred equation in 2005. However, if body fat percentage is known, the Katch-McArdle equation can be more accurate for individuals at the extremes of body composition — very lean or significantly above average body fat — because it uses lean body mass as its sole input.
Why do Harris-Benedict and Mifflin-St Jeor give different results?
The two equations were developed decades apart using different study populations and statistical methods. Harris-Benedict dates to 1919 (revised by Roza and Shizgal in 1984) and was based on a smaller, less diverse sample. Mifflin-St Jeor (1990) used 498 healthy adults and modern regression techniques. The original Harris-Benedict equation systematically overestimated BMR; the 1984 revision corrected some but not all of that bias, which is why it still tends to run 50–100 kcal higher than Mifflin-St Jeor for most inputs. For an in-depth formula accuracy comparison, the accompanying blog post reviews validation data from both equations.
When should I use the Katch-McArdle equation instead?
Katch-McArdle is most valuable when body composition deviates significantly from average. For a very lean person (under 12% body fat for males or under 20% for females), the weight-based formulas may underestimate BMR because a higher proportion of that weight is metabolically active muscle. Conversely, for someone with above-average body fat, weight-based formulas may overestimate BMR because fat tissue requires less energy than muscle. In both cases, Katch-McArdle adjusts for this by calculating from lean mass alone. You will need a reasonably accurate body fat measurement — use the body fat estimation tool if you do not have a recent reading.
Does BMR change as I lose or gain weight?
BMR changes with every shift in body weight and composition. Losing weight reduces the total tissue the body must maintain, which lowers BMR. Gaining muscle increases the proportion of metabolically active tissue, which raises BMR. Beyond simple weight change, sustained calorie restriction can lower BMR more than weight loss alone would predict — a phenomenon called metabolic adaptation or adaptive thermogenesis. Recalculating BMR after every 3–5 kg change in body weight helps keep estimates current.

Sources

  1. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51(2):241-247.
  2. Roza AM, Shizgal HM. The Harris Benedict equation reevaluated: resting energy requirements and the body cell mass. Am J Clin Nutr. 1984;40(1):168-182.
  3. Katch F, McArdle WD. Introduction to Nutrition, Exercise, and Health. 4th ed. Philadelphia: Lea & Febiger; 1983.

About the Author

Dan Dadovic holds a PhD in IT Sciences and builds precision calculators based on peer-reviewed formulas. He is not a doctor, dietitian, or certified personal trainer — PeakCalcs provides estimation tools, not medical or nutritional advice.

BMR Calculator — Compare 3 Equations | PeakCalcs | PeakCalcs