Monte Carlo Simulation
What Monte Carlo simulation is
Monte Carlo simulation is a statistical method borrowed from physics and applied to retirement planning. Instead of assuming a fixed 7% annual return (as most free calculators do), Monte Carlo generates thousands of randomised sequences of annual returns — some great years, some terrible ones, in random order — and asks: across all of these sequences, in what percentage does the plan not run out of money before the target end age?
That percentage is the probability of success.
Why it matters for retirement planning
A plan showing “you’re on track” in a linear calculator (Fidelity Retirement Score, Vanguard Nest Egg, Bankrate) typically has a 60-70% success probability when run through Monte Carlo. The same plan at 90% Monte Carlo success probability is a meaningfully different, more conservative plan.
The gap exists because of sequence-of-returns risk — the order of market returns matters enormously in retirement. Two retirees with identical average returns over 30 years can have wildly different outcomes depending on whether the bad years come early or late. If the bad years come in the first 5 years of retirement, portfolio depletion can be irreversible. A fixed-return calculator cannot model this. Monte Carlo can.
See our full explainer: Monte Carlo simulation in retirement planning explained.
Which tools use Monte Carlo
| Tool | Monte Carlo | Run count | Notes |
|---|---|---|---|
| FIRECalc | Historical sequences | N/A | Uses actual historical returns, not randomised |
| cFIREsim | Historical sequences | N/A | Similar to FIRECalc; FIRE community standard |
| ProjectionLab | Yes | 10,000 | Highest run count in the $0-$200/yr tier |
| Boldin PlannerPlus | Yes | 1,000 | Lower run count but paired with better tax modelling |
| Pralana Online | Yes | High | Actuary-built; run count not publicly disclosed |
| Maxifi | No (lifecycle model) | N/A | Different approach — optimises across scenarios rather than reporting % success |
| Fidelity Retirement Score | No | N/A | Linear projection |
| Vanguard Nest Egg | No | N/A | Linear projection |
What a good probability of success looks like
There is no universal threshold, but these rough guidelines are commonly cited:
- Below 80%: Most financial planners would flag this plan for adjustment
- 80-89%: Reasonable for someone with flexibility (can reduce spending or work part-time)
- 90-95%: Generally considered secure for most retirement horizons
- Above 95%: Often indicates an overly conservative plan — potentially leaving significant money unspent
The right target depends on your risk tolerance, flexibility, and how long your retirement horizon is. A 60-year FIRE horizon needs a higher threshold than a 25-year conventional retirement.
Primary sources
- Bengen, W. P. (1994). “Determining withdrawal rates using historical data.” Journal of Financial Planning. — the originating study for the 4% rule and the catalyst for Monte Carlo adoption in retirement planning
- SSA.gov actuarial life tables — used to calibrate retirement horizon assumptions in Monte Carlo tools
- CFPB retirement planning resources — CFPB guidance on evaluating retirement planning tools