Monte Carlo Simulator
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Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
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About Monte Carlo Simulator
Run Monte Carlo simulations and what-if scenarios on your CSV, in the browser.
Turn a spreadsheet into a risk model. Pick an outcome column (revenue, margin, churn, load) and the numeric drivers behind it; the tool fits a linear model, then runs up to 20,000 Monte Carlo iterations while sampling each driver from a distribution you control with a slider.
You get the full picture instead of a single guess: a probability distribution of the outcome, P10 / P50 / P90 percentiles, explicit best-case / median / worst-case scenarios, before-vs-after KPI cards, and a tornado chart that ranks which assumption moves the result the most. Adjust a slider and every chart updates instantly.
Everything runs locally in your browser — your data is never uploaded. Runs are seeded, so the same inputs always give the same numbers.
Category: AI & Machine LearningCommon Use Cases
- Modeling the range of likely annual revenue given uncertain price, volume and churn
- Finding which cost driver contributes most risk to projected margin
- Stress-testing a budget against best- and worst-case demand
Key Features
- Up to 20,000 Iterations
- Per-Driver Distribution Sliders (Normal / Uniform / Triangular)
- Outcome Distribution + P10/P50/P90
- Best / Median / Worst Scenario Table
- Tornado Sensitivity Chart
- Seeded & Reproducible
- Runs 100% In-Browser
The Monte Carlo Simulator tool is compatible with: Financial Models, Sales Pipelines, Budget Sheets, Project Estimates.
Use Regression or Correlation first to confirm which columns actually drive your outcome, then bring them here to simulate the range of results; send a chosen scenario into Forecast to project it over time.
Frequently Asked Questions
Instead of computing one result from fixed inputs, it runs the calculation thousands of times while drawing each uncertain input at random from a distribution. The spread of the results tells you how likely each outcome is.
No. The tool fits a linear model from your historical rows automatically. You choose the outcome column and the driver columns; it estimates the relationship and its residual noise.
No. The simulation runs entirely in your browser. Nothing is sent to a server.
Yes. The random number generator is seeded, so the same dataset and slider settings always produce the same percentiles.
Built for analysts and planners who need a defensible range — not a single point estimate — without setting up an @RISK spreadsheet or writing a NumPy notebook.
Read the related guide →