Retirement Calculator

This calculator begins with the annual spending amount you enter in today’s dollars. It adds your inflation assumption through the planned retirement date, subtracts any other monthly income you enter, and divides the remaining annual spending gap by the withdrawal rate you enter. The result is a planning target for that exact scenario.

No single retirement number works for every person. Changing the retirement date, income source, spending amount, inflation assumption, or withdrawal rate changes the arithmetic. The page should make those inputs easy to challenge, because a model that hides them can look more certain than it is.

Before an inflation adjustment, if a scenario has $48,000 of annual spending and $12,000 of other annual income, the annual gap is $36,000. With a user-entered 4% withdrawal-rate assumption, $36,000 ÷ 0.04 = $900,000. That is not a recommendation to use 4%, an assurance that $900,000 will be sufficient, or a forecast of expenses. It is simply the visible division that the model performs.

The page then adds the age and inflation assumptions. The retirement-year spending gap can be larger or smaller than the today-dollar illustration, and the result changes when you change a rate or date. Use the diagram to trace that chain instead of accepting one headline result.

Before retirement, the calculator grows the entered current savings and contributions using the return assumption you choose. During retirement, it applies the separate retirement return, spending withdrawals, other income, inflation, and plan-to age. A difference in any one assumption can change the displayed balance path, especially over a long time horizon.

The U.S. Securities and Exchange Commission describes retirement planning tools as estimates built from assumptions. That is the right framing here. The modeled “money lasts until” result is not a promise that an account will support a real withdrawal plan; it is the output of the selected assumptions and sequence.

Try changing one input at a time. Keep savings, contribution, and planned retirement age constant; then test a different return or inflation assumption. Next, restore those values and adjust only the spending goal or other income. This makes it clear which assumption is doing the work in the result.

Do not interpret the “required monthly” field as a personalized savings instruction. It is the deposit that closes the model’s gap under its current rates and dates. Account limits, taxes, employer matching, benefits, debt, emergency savings, health costs, and risk tolerance can all change a real plan. Use the Investment Calculator for a narrower contribution-growth scenario and the Savings Goal Calculator for a date-and-deposit question.

Enter only income figures you can explain and revisit. A pension estimate, government-benefit estimate, rental income, or part-time work assumption can have eligibility rules, taxes, indexing, timing, and uncertainty that this page does not verify. The calculator simply subtracts the monthly amount you supply from the spending gap in the scenario.

Keep a record of the source date and terms behind each number. For household spending inputs, start with a current plan in the Budget Calculator. If the retirement scenario is important to a decision, confirm benefit and account details with the relevant provider and obtain appropriately qualified advice.

Write down the origin and date of each major input: current account balance, planned contribution, spending estimate, other income estimate, return assumptions, inflation assumption, withdrawal rate, retirement age, and plan-to age. If an input is only a rough placeholder, mark it that way. A transparent list makes the projection easier to revise when a provider updates a benefit estimate, expenses change, or a contribution becomes unavailable.

Run at least one alternate scenario rather than relying on the most comfortable output. Alter one input at a time and observe whether the model is primarily driven by spending, time, return, or withdrawal assumptions. This does not create certainty; it reveals which unknowns deserve the most careful real-world verification.