How to FORECAST in Excel Based on Historical Data

What this does

FORECAST.LINEAR predicts one y for one x by fitting a least-squares line through the known points. It is identical to computing INTERCEPT plus SLOPE times x, just in one call. The newer FORECAST.ETS handles seasonal time series with exponential smoothing and needs a proper date column; the plain linear form assumes a straight-line relationship and nothing more. The legacy FORECAST still works and matches FORECAST.LINEAR. As with any regression, predictions far outside the observed range of x are extrapolation rather than forecasting. The same idea underpins a lot of everyday Excel work, so the few minutes spent getting it right here pay back across every sheet you build afterwards. Treat it as a pattern, not a one-off, and it stops being something you look up and starts being something you reach for. Treat “forecast in excel based on historical data” as a small repeatable workflow rather than a one-off click you hope to remember next time. Use a small test block before the live file, so any surprise in the affected cells shows up while it is still harmless. When a formula is involved, keep the inputs labelled beside it, reference cells instead of typing values, and apply number formatting only after the result checks out. That turns a calculation you can defend to a CFO or an auditor into a method you can reuse, explain, and defend when the workbook leaves your screen.

A worked example

Months 1 to 24 in A2:A25 and revenue in B2:B25: =FORECAST.LINEAR(25, B2:B25, A2:A25) predicts month 25. For a seasonal series with real dates, =FORECAST.ETS(newDate, B2:B25, A2:A25) captures the repeating pattern a straight line cannot. FORECAST puts a defensible projection in a cell instead of a chart annotation, which is what a planning model needs. A practical tip before you scale it up: build it once on a small block of test data, confirm the number against the tool on this page, and only then point it at your real sheet. That one habit catches almost every mistake while it is still cheap to fix, long before a wrong figure reaches a report or a colleague.

In Google Sheets

Google Sheets handles this almost identically to Excel. The formula syntax above is the same, and the menu lives under a slightly different label rather than a ribbon tab. Use the platform toggle at the top of the page to switch every keyboard shortcut between Windows and Mac, and expect at most cosmetic differences in naming. The aim was to get you unstuck fast and leave you a little more capable than a copy-paste would. The answer is at the top and the detail above shows why it holds — so the next time a colleague asks, you can answer without reaching for search. Here is the takeaway for “forecast in excel based on historical data”: copy the answer if you are busy, but if you have a spare few minutes, rebuild the example in Excel yourself with the tool above open beside it. That single pass — type it, run it, watch the result move when you change an input — is what turns a formula you found into a technique you trust. Keep your inputs labelled and referenced, never hard-coded, and the same sheet stays correct and auditable as it grows. Done that way, you will not need to look this up again, and you will be the person others ask.

Common mistakes

• Predicting far outside the range of the historical x values, where the fitted line carries no evidence.
• Using the linear form on a seasonal series; FORECAST.ETS exists for that and needs evenly spaced dates.
• Mixing up the argument order — the x to predict comes first, then y values, then x values.

Frequently asked questions