How to Use Monte Carlo Simulation for Retirement Planning

3.9%. Morningstar's 2025 research puts the safe starting withdrawal rate at that level, meaning it held up in 90% of simulated futures over a 30-year retirement. Look at how it was judged. Morningstar didn't ask what an average return would produce. It asked how often the money was still there at the end. That's the core of using Monte Carlo simulation for retirement planning. You run your own plan through many possible futures, count how many stay funded, and adjust until the odds are ones you can live with. (Source: Morningstar, The State of Retirement Income 2025, December 2025.)

In short: enter your numbers, read the result as a probability, change one thing at a time, and rerun the plan as your life changes. The rest of this guide covers each step and the parts most explainers leave out.

What a Monte Carlo simulation actually does

The name sounds technical. The idea isn't.

A standard retirement projection picks one average return, say a steady gain every year, and draws a smooth line. Real markets don't move that way. Some years are up and some are down, and the order of those years matters. A bad stretch right after you start withdrawing hurts much more than the same stretch twenty years later.

A Monte Carlo simulation deals with that by generating many different market paths: good decades, bad decades, and everything between. Your plan runs through each one, and the simulation counts how many paths end with money left over. Different tools run different numbers of paths. MyPlanIQ's simulator, for example, runs 10,000 iterations (MyPlanIQ). The plan you build with Monte Climb runs 1,000.

The result is a success rate. If 800 of 1,000 futures stay funded, your plan succeeds 80% of the time under the model's assumptions.

That's a probability, not a promise.

How to use Monte Carlo simulation for retirement planning, step by step

Step 1: Start with three numbers

You need very little to get a first answer:

• Your age
• What you've saved for retirement
• What you spend each month

That alone puts you ahead of many people. EBRI's 2025 Retirement Confidence Survey found that only 52% of workers have estimated the monthly income they'll need in retirement, so about half are guessing (Source: EBRI/Greenwald, Retirement Confidence Survey 2025, Fact Sheet 3).

More detailed tools also ask for asset allocation, expected returns and volatility, inflation, and the length of retirement (Validea, White Coat Investor). Those inputs add precision. They aren't needed for a first look.

Step 2: Plan for a longer life than feels natural

People often get the time horizon wrong. According to Social Security's planning guidance, about one in three 65-year-olds may live to at least age 90 (Source: Social Security Administration, Retirement Information for Medicare Beneficiaries, 2026).

A plan that stops at 85 is quietly betting against a third of retirees. That's why plans built in Monte Climb run to age 95 by default, and you can extend them further. Whatever tool you use, check where its plan ends.

Step 3: Count the costs people forget

Health care is a real expense in retirement, not a rounding error. Fidelity estimates that a 65-year-old retiring in 2025 will need $172,500 for Medicare premiums, deductibles, and prescriptions over retirement, and that figure doesn't include long-term care (Source: Fidelity Investments, 2025 Retiree Health Care Cost Estimate, July 2025).

If your monthly spending figure leaves out health care, your success rate will look better than it should. Our engine charges Medicare premiums and income-based surcharges year by year instead of using one flat guess.

Step 4: Read the success rate correctly

Say your plan comes back at 72%. That means:

• In 72% of simulated futures, your money lasted to the end of the plan.
• In 28%, it ran out at some point.

It doesn't mean you have a 28% chance of being broke. Many of those "failures" run short late in the plan, and in real life you would react long before then by trimming spending, delaying a big purchase, or adjusting withdrawals. More on that below.

Step 5: Change one lever at a time

Here, the simulation stops being a report card and becomes a planning tool. Change one input, rerun, and compare the results:

Changing a single input shows you which change actually moves your number. Changing several at once makes it impossible to tell what helped.

Step 6: Break your plan on purpose

Don't stop at the result you hoped for. Stress-test it. Try higher spending, an earlier retirement date, or a longer life. The aim is to find out where the plan breaks before life finds out for you.

What success rate should you aim for?

There's no single correct number, and anyone offering one without context is oversimplifying.

Morningstar's research uses 90% as its benchmark for a "safe" withdrawal rate. That's a cautious standard, and it suits someone whose spending is mostly fixed.

Other researchers say a high target can cost you. Michael Kitces argues that a 50% probability of success, or even lower, may be reasonable for retirees who are willing to adjust their spending along the way (Kitces). His reasoning: a plan that "succeeds" in nearly every future often means you spent less than you could have.

One way to think about it:

• Rigid spending (fixed bills, little room to cut): lean toward a higher success rate.
• Flexible spending (a big share is discretionary, like travel or gifts): a lower rate may be acceptable, because you'd adjust if markets turn.

Where you land depends on your circumstances. This is planning software, not advice, so treat these as questions to work through, not rules.

What the success rate doesn't tell you

The top-ranking pages mostly stop at the success rate. These four limits are worth understanding.

1. How badly a plan "fails"

A pass/fail number treats running out at 94 the same as running out at 75. The CFA Institute points out that this misses how far short a plan falls. In its example, a plan with a 50% success rate still covered 90% of the spending goal on average (CFA Institute).

So a "coin flip" result can be less alarming than it sounds.

2. Which model is running underneath

Not all Monte Carlo simulations work the same way. A study by Derek Tharp and Justin Fitzpatrick, published through Income Lab and Kitces, compared several approaches against real historical outcomes. Traditional Monte Carlo, the model most advisor software uses, had more forecast error than the alternatives. Historical simulation was the most accurate at commonly used success levels. No method had error close to zero (Kitces, Income Lab).

The point isn't to distrust simulation. It's to treat any single result as an estimate with real uncertainty around it.

3. The assumption that spending stays flat

Most calculators assume you'll spend the same inflation-adjusted amount every year until the end. Research suggests most people don't.

David Blanchett's "retirement spending smile" found that real spending tends to fall about 1% a year, speeding up to about 2% a year in the middle of retirement, then rising late in life while still declining overall (FPA Journal, May 2014). Earlier work by Fisher and colleagues, which Blanchett cites, found consumption drops about 2.5% at retirement and about 1% a year after that (FPA Journal PDF).

If your tool assumes flat real spending, your success rate may be somewhat conservative. That's a useful margin, but it's worth knowing it's there.

4. A single run is only a snapshot

ThinkAdvisor and others warn against running one analysis and treating it as settled (ThinkAdvisor). Markets move, your balance changes, and your plans shift. A result from three years ago describes a plan you no longer have.

When to rerun your simulation

"Rerun it regularly" is common advice, but few sources say when. A simple schedule:

• Once a year, at a fixed time, such as your birthday or tax season.
• After a big market move, up or down.
• After a life change: retirement date, health, a home sale, an inheritance, a change in spending.
• Before a major decision, such as claiming Social Security or a large one-time purchase.

Some planners take this a step further with guardrails: preset rules that trigger a spending cut if your success rate falls below a floor, or a raise if it climbs above a ceiling (Kitces). That turns a single number into an ongoing system for adjusting spending.

Put it to work on your own numbers

Using Monte Carlo simulation for retirement planning comes down to a few habits:

1. Start with honest inputs, including health care.
2. Plan for a long life.
3. Read the result as odds, not a guarantee.
4. Change one lever at a time.
5. Rerun when life or markets change.

When can you actually retire? You won't get a certain answer, but you can get a much better estimate.

You can run your three numbers through 1,000 simulated futures in your browser, and nothing is saved until you choose to save it. Then ask William, our AI planner, follow-up questions like "Am I on track?" or "Can I retire at 62?" He shows his work.

Show my answer →

Frequently asked questions

What is a Monte Carlo simulation in retirement planning?

It's a method that runs your savings, spending, and timeline through many simulated market paths, including good and bad sequences of returns, and counts how often your money lasts. The result is a success rate, which is a probability, not a guarantee.

What is a good Monte Carlo success rate for retirement?

There is no single right number. Morningstar's 2025 safe withdrawal research uses a 90% benchmark, which is cautious. Michael Kitces argues that 50% or lower may be reasonable for retirees willing to adjust their spending. The more flexible your spending, the lower a rate you may be able to accept.

Is Monte Carlo simulation accurate for predicting retirement outcomes?

It's useful, but it isn't precise. A study by Tharp and Fitzpatrick, published through Income Lab and Kitces, found that traditional Monte Carlo had more forecast error than other methods, historical simulation was the most accurate at common success levels, and no method had error near zero. Treat any result as an estimate and rerun it over time.

Does a 70% success rate mean a 30% chance of running out of money?

Not quite. It means that in 30% of simulated futures the money ran out at some point, often late in retirement, if you never changed course. In real life you can cut spending or adjust withdrawals along the way. CFA Institute research also shows that 'failed' plans often still cover most of the spending goal.

How often should I rerun my retirement Monte Carlo simulation?

A reasonable rhythm is once a year, plus after any big market move, a major life change such as health, a home sale, or a new retirement date, and before big decisions like claiming Social Security.