Best Free Retirement Calculator With Monte Carlo Simulation

A 73.7% success rate. That is the result one calculator shows for a 4% withdrawal from a 60/40 portfolio over 30 years. It means about 263 of 1,000 simulated retirements ran out of money (Western & Southern, Retirement Confidence Calculator). Is that good? Bad? Most "best of" lists won't tell you. So here is the short answer. The best free retirement calculator with Monte Carlo simulation is one whose method you understand, that asks for inputs you actually have, and whose success rate you know how to read. Below we compare the main options, then cover what the rankings leave out.

The short answer: which calculator fits which person

No single tool wins for everyone. They use different methods, and they ask for different amounts of effort.

FIRECalc and cFIREsim test your plan against every historical market period back to 1871 (ChooseFI, early retirement calculators). Boldin puts Monte Carlo in its paid PlannerPlus tier (Boldin, The 10 Best Retirement Calculators). Prices for that tier differ from source to source, so check Boldin's site before you rely on any figure.

A caution about those comparisons. Many of the pages ranking these tools are written by the companies that make them. Read every list with that in mind, including this one.

What a Monte Carlo calculator actually does

In plain terms, it rolls the dice thousands of times.

A simple calculator assumes one average return, maybe 6% a year, every year. Real markets don't work that way. You might get three strong years and then a crash, or the crash might come first. That order matters a lot when you're withdrawing money, because selling during a downturn locks in losses.

A Monte Carlo simulation builds many possible futures with different sequences of returns. It runs your plan through each one and counts how many end with money left. That count is your success rate.

There are three main ways tools generate those futures:

• Historical backtesting (FIRECalc, cFIREsim): uses real past return sequences.
• Parametric Monte Carlo (Empower, Fidelity): draws random returns from a statistical model.
• Forward-looking assumptions (QuantCalc, Portfolio Lab): builds in lower or different expected returns than history shows.

None of these is "the right one." Each answers a slightly different question.

How to read a success rate (what the rankings skip)

This is the part most lists leave out. A success rate is pass/fail. A future counts as a success if the balance is above $0 at the end. If it hits zero, it's a failure.

Retirement researcher David Blanchett put the problem bluntly: "You could accomplish your goal entirely up until the last year of retirement and fall a dollar short, and you would be defined as failing" (401k Specialist, Success Rates Fall Short for Major Retirement Decisions).

So a 73.7% success rate doesn't mean a 26.3% chance of disaster. Some of those "failures" run dry at 94 after decades of comfortable spending. Others run dry at 78. The success rate on its own doesn't tell them apart.

When you look at any result, ask:

1. How late do the failures happen? A shortfall in the final year or two is a very different problem from one in your 70s.
2. How big is the shortfall? Missing a small amount is not the same as missing half your spending.
3. What would I change if things went badly? Most simulations assume you never cut spending. Real people do.

What success rate should you aim for?

Higher isn't always better. A 99% success rate can mean you're underspending for decades to guard against a rare bad outcome.

One practical framework comes from Michael Kitces's work on probability-based guardrails. Start with a plan at about a 95% success rate. If the rate later rises above 99%, you can probably spend more. If it falls below 70%, you trim spending (Kitces, retirement income guardrails and Monte Carlo).

The point is that a success rate isn't a grade you get once. You check it again over time and adjust.

Research on withdrawal rates points the same way. Morningstar's 2025 research puts the safe starting withdrawal rate at 3.9%, defined as the rate where money is still there in 90% of simulated outcomes over a 30-year retirement (Morningstar, The State of Retirement Income 2025, Dec 2025). It's measured by odds, not by an average return.

What most simulations leave out

In most tools, investment returns are the only thing that changes randomly from run to run. Blanchett makes this point too (NAPA, Feb 2023). Everything else is usually fixed:

• Inflation is often a single assumed rate.
• Spending is assumed to stay steady, even through a crash.
• Lifespan is one fixed end date.

That last one matters more than it looks. According to the Social Security Administration, about one in three 65-year-olds may live to 90 or beyond (SSA, Retirement Information for Medicare Beneficiaries, 2026). A plan that ends at 85 is quietly betting against a third of retirees.

The opposite mistake also costs you. Kitces notes that a very long, conservative lifespan assumption lowers your success rate on its own, which can push you to underspend (Kitces, What's Your Longevity Assumption?). Know what end age your calculator uses, and try a few.

Health care is the other big blind spot. Fidelity estimates that a 65-year-old retiring in 2025 will spend $172,500 on Medicare premiums, deductibles, and prescriptions over retirement, and that figure leaves out long-term care entirely (Fidelity Investments, 2025 Retiree Health Care Cost Estimate, Jul 2025). A calculator that folds this into one flat "spending" number may understate it.

Monte Carlo vs. historical: not simply "safer vs. riskier"

Many roundups treat the two methods as interchangeable, or assume Monte Carlo is automatically the more cautious choice. It isn't always. Income Lab's research finds that at commonly used settings, Monte Carlo can understate retirement income risk compared with historical simulation (Income Lab, How Monte Carlo Can Understate Retirement Income Risk).

What that means for you: don't expect two tools to agree. Put the same numbers into a historical tool and a Monte Carlo tool. If both say your plan works, you can be more confident. If they disagree, that gap tells you how sensitive your plan is to the assumptions.

Five questions to ask before you trust any calculator

1. Is the Monte Carlo actually free, or is it behind a paywall or a customer login?
2. What method does it use? Historical, parametric, or forward-looking?
3. What end age does the plan run to, and can you change it?
4. How does it handle health care costs? As a separate cost, or folded into spending?
5. Does it explain the result, or just show a percentage?

Where Monte Climb fits

Full disclosure: this is our product, so weigh what follows the same way you'd weigh any vendor's list.

Our calculator asks for three numbers: your age, what you've saved for retirement, and what you spend each month. It runs them through 1,000 simulated futures, using the same engine behind the app, and returns one answer: how many of those futures stay funded. It runs in your browser, and nothing is saved until you choose to save it.

A few design choices follow from the research above:

• Plans run to age 95 by default, and you can push them further, because of the SSA longevity data.
• The engine charges Medicare premiums and income-based surcharges year by year instead of using a flat guess.
• The result is a probability, not a promise. It's planning software, not advice.

If you want to go further, you can ask William, our AI planner, follow-up questions like "Am I on track?", "Can I retire at 62?", or "What's a sustainable spend?" He shows his work, and you can talk to him the way you'd talk to a friend. The full app comes with a 7-day trial for $1.

It's a sensible first step. EBRI's 2025 Retirement Confidence Survey found that 48% of workers have never estimated the monthly income they'll need in retirement (EBRI/Greenwald, Retirement Confidence Survey 2025, Fact Sheet 3). Half of workers are guessing. Three numbers get you past that.

Run your own numbers

The best calculator is one you'll actually use, and whose answer you understand. Try two methods, look past the headline percentage, and check your plan again every year or so.

When can you actually retire? Start with three numbers. Show my answer

Frequently asked questions

What is the best free retirement calculator with Monte Carlo simulation?

It depends on what you need. FIRECalc and cFIREsim test your plan against market history back to 1871. Empower runs random simulations using your linked accounts. Newer tools like QuantCalc and Portfolio Lab use forward-looking return assumptions. Pick one whose method you understand, and try a second method to compare.

What is a good Monte Carlo success rate for retirement?

There's no single correct number. One framework from Kitces suggests starting a plan at about a 95% success rate, then spending more if the rate rises above 99% and trimming spending if it falls below 70%. Aiming for 99% or higher can mean underspending for years.

What does a 75% Monte Carlo success rate mean?

It means about 750 of 1,000 simulated futures ended with money left. The measure is pass/fail, so a plan that runs one dollar short in its final year counts as a failure. Look at when and by how much the failing futures fall short, not only at the percentage.

Is Monte Carlo more accurate than historical backtesting?

Neither is strictly more accurate. Each answers a slightly different question. Income Lab's research finds that at common settings, Monte Carlo can understate risk compared with historical simulation. Running both methods and comparing the results shows how sensitive your plan is to assumptions.

What do Monte Carlo retirement calculators leave out?

In most tools, investment returns are the only thing that varies randomly. Inflation, spending, and lifespan are usually fixed, and most tools assume you never cut spending in a downturn. Health care costs may also be folded into general spending instead of modeled separately.