In Excel: use =FORECAST.LINEAR(x, known_ys, known_xs) — it predicts a single value from a straight-line fit through your historical points.
Syntax
Arguments
| Argument | Description | |
|---|---|---|
x | required | The point to predict a value for. |
known_ys | required | The observed outcomes. |
known_xs | required | The observed inputs, the same size as known_ys. |
Related functions
Select the result cell and type =FORECAST.LINEAR(.
Enter the x value you want a prediction for, then a comma.
Select the known y values, a comma, then the known x values.
Press Enter. Chart the actuals with the prediction to sanity-check the line.
Need it as an auditable file?
Ships inside the linked template — formula-driven, unlocked, audit-ready.
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. Most people learn this as a sequence of clicks and forget it by next week; learning it as a pattern instead is what lets you apply it to the next, slightly different version of the problem without starting from scratch. That is the difference this page is trying to make. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “cash forecast template excel”. Start on a copy or a tiny sample, keep the affected cells visible, and compare the result with the tool above before you touch the real workbook. 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. The point is a calculation you can defend to a CFO or an auditor, but the practical win is that someone else can open the file and understand what happened without asking you.
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. One habit worth forming early: name the cells that hold your inputs, so the formula reads in plain language instead of a string of cell addresses. A reviewer — or you in three months — can then follow the logic without decoding what B7 and D2 were supposed to mean, which is most of what makes a sheet maintainable.
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. Keep this page bookmarked for the next time the same question comes up. Better still, rebuild the example once in your own sheet — doing it yourself, with the tool above to check against, is what turns a copied formula into a technique you own. If you take one thing from this page on “cash forecast template excel”, make it the habit rather than the keystrokes: set the problem up with labelled inputs, reference those cells, and let Excel do the recomputing. Bookmark the page for the syntax, but do the example once in a blank sheet and check it against the tool above — five minutes of hands-on practice fixes the method in memory far better than re-reading, and it surfaces the small snags while they are still harmless. After that the technique is genuinely yours: faster than searching for it again, and reliable enough to drop into work that other people depend on.
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
What is the difference between FORECAST and TREND?
FORECAST returns one predicted value; TREND returns a whole array of them, and also supports multiple independent variables.
When should I use FORECAST.ETS?
When the data is a time series with a repeating seasonal pattern and evenly spaced dates. The linear form cannot represent seasonality.
Is FORECAST the same as SLOPE plus INTERCEPT?
Yes — =FORECAST.LINEAR(x,ys,xs) equals =INTERCEPT(ys,xs)+SLOPE(ys,xs)*x exactly.