In Excel: give FORECAST.LINEAR only the two bracketing points — =FORECAST.LINEAR(x,{y1;y2},{x1;x2}) — and it returns the straight-line value between them.
Sort the table by the x column ascending; everything below depends on that order.
Locate the row below the target with =MATCH(E2,$A$2:$A$13,1), which returns the position of the largest x not greater than the target.
Use INDEX with that position and the one after it to build the two-point ranges for FORECAST.LINEAR.
Or compute it arithmetically: y1 + (x - x1) * (y2 - y1) / (x2 - x1), which makes each term visible on the sheet.
Guard the edges with IF so a target outside the table returns a message rather than a silent extrapolation.
What this does
Interpolation estimates a value at an input that lies between two measurements, on the assumption that the relationship is straight between them. Passing FORECAST.LINEAR the whole table instead of the bracketing pair does something quite different: it fits a least-squares line through every point and returns a value from that fit, which is a regression estimate rather than an interpolation. 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. Treat “linear interpolation excel” 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 visual that makes the number obvious at a glance into a method you can reuse, explain, and defend when the workbook leaves your screen.
A worked example
Viscosity is 4.2 at 20 °C and 3.1 at 30 °C. At 24 °C the interpolated value is 4.2 + (24-20) × (3.1-4.2) / (30-20) = 3.76, and =FORECAST.LINEAR(24,{4.2;3.1},{20;30}) returns the same 3.76. Handing the function all twelve rows of the table would return 3.68 — a different number answering a different question. Rate tables, calibration curves and price breaks are all published at intervals, and reading the nearest row instead of interpolating is a rounding error nobody documents. 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
Everything above works in Google Sheets too. Excel and Sheets share the formula syntax used here; only the surrounding menus are arranged differently. That portability is deliberate — learn it once and it follows you between the two tools and across Windows and Mac. 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 “linear interpolation 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
- Passing the entire dataset to FORECAST.LINEAR and calling the result an interpolation.
- Leaving the x column unsorted, which makes
MATCHwith match type 1 return the wrong bracketing row without any error. - Extrapolating past the ends of the table, where a straight-line assumption has nothing supporting it.
- Interpolating a curved relationship over a wide gap — fit a curve, or interpolate between closer points.
Frequently asked questions
Is FORECAST.LINEAR the same as TREND?
For a single new x they return the same value. TREND accepts an array of new x values and returns an array of results.
How do I find the two rows to interpolate between?
MATCH with match type 1 on a sorted x column gives the row below; the row after it is the upper bracket.
What about non-linear data?
Add a trendline, tick Display Equation on chart, and evaluate that equation — or interpolate between points close enough together for a line to be reasonable.
Can I interpolate a date?
Yes. Dates are numbers, so a date x column works directly, as long as the cells are real dates rather than text.
Other ways people ask this
On the way here you may have searched this as “linear trend interpolation excel” and “excel linear interpolation formula” — it is all the same task, and this page is the single, complete answer to it.
Why do people search for this in so many different ways?
Because the same task has many names. “linear trend interpolation excel”, “excel linear interpolation formula” all point at the one operation explained on this page, which is why they all lead here.