Suggested next steps
Continue this workflow
Move to a practical next or previous step without transferring your entered values.
About One-Rep Max Calculator: 1RM Strength Estimator
One-Rep Max Calculator estimates your maximum single-repetition lifting capacity from submaximal repetitions to fatigue.
It computes consensus strength benchmarks using validated exercise physiology equations including Epley, Brzycki, and Lander models.
How the calculation works
Epley equation
1RM = Weight × (1 + Reps / 30).
Brzycki equation
1RM = Weight × (36 / (37 − Reps)).
Percentage training zones
Calculates 95%, 90%, 85%, 80%, and 70% submaximal working sets for periodized resistance training.
How to use this calculator
- 1Enter the weight lifted in kilograms or pounds.
- 2Enter the completed repetitions performed to failure (ideal between 2 and 10 reps).
- 3Select your preferred prediction equation (Consensus Average, Epley, or Brzycki).
- 4Review your estimated 1RM and percentage load breakdown for programming training cycles.
Understanding the result
Estimates are most accurate between 2 and 10 repetitions; as repetitions exceed 10, muscular endurance skews the neuromuscular maximum estimate.
Use 1RM percentages to program periodized training blocks (e.g. 70–80% for hypertrophy, 85–95% for maximal strength).
Important limitations
- Formulas assume full range of motion and standardized lifting technique.
- Individual muscle fiber composition (slow-twitch vs fast-twitch dominance) can cause variation in rep-max performance.
Explore this topic
Frequently asked questions
Why estimate 1RM instead of testing true 1RM?
Testing true 1RM lifts poses significant joint strain and injury risk. Submaximal estimation offers a safer benchmark for tracking strength progression.
Which formula is most accurate?
The consensus average of Epley and Brzycki is widely recognized as the most balanced predictor across bench press, squat, and deadlift.
Is my workout data uploaded?
No. All calculations run strictly in your web browser.
Related tools
Selected from curated relationships first, then the same subtopic and category.