Estimate your one rep max using the Brzycki formula. More conservative than Epley at higher reps. Enter weight and reps for your 1RM prediction.
The Brzycki formula is a common way to estimate a one-rep max from a submaximal set.
Compared with Epley, it tends to give slightly more conservative estimates as rep counts rise. This calculator applies the formula, shows a percentage chart, and lets you compare the result with other common estimates.
It is best used with submaximal sets rather than very high-rep fatigue work.
It is useful if you want a conservative 1RM estimate without attempting a true max. The result works best as a programming reference rather than as a literal tested maximum.
Brzycki Formula: 1RM = weight × (36 / (37 − reps)) Example: 225 lbs × (36 / (37 − 5)) = 225 × (36/32) = 225 × 1.125 = 253.1 lbs Note: The formula is undefined at 37 reps (division by zero) and produces negative values above 37 reps. Practical range: 1–12 reps.
Result: Estimated 1RM (Brzycki): 253.1 lbs | Epley comparison: 262.5 lbs | Difference: −9.4 lbs
Using 225 lbs for 5 reps: Brzycki gives 225 × (36/(37−5)) = 225 × 1.125 = 253.1 lbs. Epley gives 262.5 lbs — a 9.4 lb difference. At 5 reps, this gap is small (3.6%), but it widens with more reps. For training, the conservative Brzycki estimate is often preferred as it reduces injury risk from overloading.
The Brzycki equation (weight × 36/(37 − reps)) creates a hyperbolic curve that approaches infinity as reps approach 37. This means each additional rep increases the predicted 1RM by an increasingly large amount, which is why the formula becomes unreliable at high reps. In contrast, Epley's linear formula (weight × (1 + reps/30)) increases the prediction at a constant rate per rep.
Many collegiate strength programs use Brzycki as their primary 1RM estimation method. Its conservative nature means that when athletes arrive at their programmed heavy singles and doubles, the weights feel achievable rather than overwhelming. This psychological factor — feeling confident under heavy weight — is underrated in training success.
Sports scientists recommend using the average of 2–3 formulas (Epley, Brzycki, Lombardi) for the most reliable 1RM estimate. This approach smooths out the mathematical biases inherent in any single formula and has been shown to fall closer to actual 1RM in validation studies.
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This worksheet applies the Brzycki equation to a submaximal set and treats the output as a conservative estimate rather than a true tested max.
At 1–4 reps, both formulas give nearly identical results (within 1–2%). At 5–8 reps, Brzycki is 2–5% lower. At 10+ reps, Brzycki becomes significantly more conservative (5–10% lower). Neither is definitively "better" — true accuracy depends on individual physiology. Using the average of both formulas is a common practical approach.
The numbers 36 and 37 come from Brzycki's regression analysis of strength testing data. The formula implies a theoretical maximum of 36 reps with zero weight (or equivalently, the 37th rep is impossible). This mathematical structure gives the formula its conservative curve at higher rep ranges.
For competition-trained powerlifters who frequently work in the 1–5 rep range, both formulas are equally accurate because the predictions converge at low reps. However, Brzycki's conservative bias makes it slightly preferred for setting training weights, as it's better to be slightly under your max than over when programming heavy singles and doubles.
You can use it for weighted bodyweight exercises by entering the total resistance (bodyweight + added weight). For unweighted exercises like push-ups or pull-ups, the formula is less applicable because the resistance is fixed and fatigue patterns differ from barbell exercises.
Yes, in practice you should round to the nearest loadable increment. Most gyms have 2.5 lb or 5 lb plates as the smallest, so round to the nearest 5 lbs. For training percentages, always round down rather than up for safety.
Every 4–8 weeks during a progressive program. Many lifters retest at the start of each training block or mesocycle. If your programming uses auto-regulation (RPE-based), you may need to retest less often since the training weights self-adjust based on daily readiness.