Monte Carlo Simulation for Retirement Readiness
Monte Carlo simulation for retirement uses probability distributions rather than fixed assumptions to model retirement outcomes — running thousands of scenarios with varying returns, inflation rates, and spending levels to produce a range of possible outcomes rather than a single projection. Understanding the probability of different outcomes is more useful for planning than a single best-guess number. This concept covers Monte Carlo simulation as the standard for rigorous retirement analysis.
HypatiaA Monte Carlo simulation runs thousands of randomized financial scenarios using variables like market returns, inflation, and spending rates to estimate the probability that your retirement savings will last through your lifetime. Rather than relying on a single average-return assumption, it shows a range of outcomes including best-case, worst-case, and median projections.
This technique was once reserved for financial advisors with specialized software, but AI can now explain the methodology, interpret simulation outputs from free tools, and help you understand what levers — savings rate, retirement age, withdrawal rate — most improve your odds.
How to apply it
Run your numbers through a free tool like FIRECalc or Portfolio Visualizer, then paste the results into ChatGPT and ask it to explain what your success rate means in plain language and identify the two or three changes that would most significantly improve your retirement probability.
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