JustilityMonte Carlo simulator
Simulate a seeded weighted sum of independent uncertain inputs with percentiles and a histogram.
Simulate a weighted sum of independent uncertain inputs. Enter distributions, coefficients, a seed and a comparison threshold.
100–100,000 trials, up to 20 independent inputs. Uniform and triangular distributions use min / max; normal uses mean / standard deviation and is unbounded. No correlations, arbitrary formulas or fitted distributions. Same seed and model reproduce results in this browser. A simulated percentile is not a confidence interval or a prediction.
Your work stays in this tab. Nothing is saved automatically. Save a readable, unencrypted project file before closing. Downloads remain wherever you save them.
Processed on your device. Your files are never uploaded by Justility.
How privacy worksHow it works
Open monte carlo simulator, enter your own project details or load the labeled example, then choose distributions and run the simulation. Review the results and download your project to continue later.
Supported formats
Editable JSON project up to 1 MB; CSV summary and histogram; up to 100,000 trials and 20 variables.
Good to know
100–100,000 trials; up to 20 independent inputs; uniform, triangular and unbounded normal distributions.
Worked example
Before
One uniform variable from 0 to 20, coefficient 1, threshold 10
After
Sample mean near 10; about half the totals at or below 10
Finite seeded samples approximate the entered model. Results vary by seed and trial count.
Monte Carlo simulator: interpret the result
Simulate a seeded weighted sum of independent uncertain inputs with percentiles and a histogram. 100–100,000 trials; up to 20 independent inputs; uniform, triangular and unbounded normal distributions. All project files are readable and unencrypted. Save and open them explicitly; there is no automatic browser persistence.
Strategy canvasTroubleshooting
Why can normal samples be below my entered mean?
The mean is a center, not a lower bound. A normal distribution is unbounded. Use uniform or triangular distributions when explicit finite bounds are needed.
Common questions
Can I use monte carlo simulator offline?
Prepare this tool using Offline help while online. After preparation, it runs locally with fresh input. Browser cache eviction remains possible; keep project downloads separately.
Can I use this without an internet connection?
Yes, after you prepare this tool from Offline help and the browser retains its assets. Installation is optional. All processing dependencies are bundled locally.