TREND extends a linear pattern into the future — project next quarter’s sales from the last few. It fits a best-fit line and returns predicted ys for the xs you give it.
The example
Projecting the next periods.
| A | B | |
|---|---|---|
| 1 | Period | Forecast |
| 2 | 5 | 22.5 |
| 3 | 6 | 25.0 |
The formula
The formula:
How it works
How it works:
TREND(known_ys, known_xs, new_xs)fits a line to the history and returns predicted ys for the new xs.- It spills a value for each new x — a whole forecast in one formula.
- For a single future point,
FORECAST.LINEAR(x, ys, xs)is simpler. - TREND assumes a straight-line pattern — check it fits before trusting the projection.
Seasonality breaks linear trends. For data with seasonal swings, FORECAST.ETS (exponential smoothing) models the pattern far better than a straight line. Use TREND for steady, roughly linear series.
Try it: interactive demo
History y values; forecast next 2.
Variations
Single point
FORECAST.LINEAR:
Seasonal forecast
Exponential smoothing:
Growth (exponential)
Curved trend:
Pitfalls & errors
Linear assumption. TREND fits a straight line; curved or seasonal data needs GROWTH or FORECAST.ETS.
Spill space. Multiple new xs spill the forecast — keep room.
Extrapolation risk. Forecasts far beyond the data are increasingly unreliable.
Practice workbook
Frequently asked questions
How do I forecast future values in Excel?
What if my data is seasonal?
How do I forecast exponential growth?
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