Often you may want to use a multiple linear regression model you’ve built in Excel to predict the response value of a new observation or data point.

Fortunately this is fairly easy to do and the following step-by-step example shows how to do so.

**Step 1: Create the Data**

First, let’s create a fake dataset to work with in Excel:

**Step 2: Fit a Multiple Linear Regression Model**

Next, let’s fit a multiple linear regression model using x1 and x2 as predictor variables and y as the response variable.

To do so, we can use the **LINEST(y_values, x_values)** function as follows:

Once we click enter, the regression coefficients appear:

The fitted multiple linear regression model is:

y = 17.1159 + 1.0183(x1) + 0.3963(x2)

**Step 3: Use the Model to Predict a New Value**

Now suppose that we’d like to use this regression model to predict the value of a new observation that has the following values for the predictor variables:

- x1: 8
- x2: 10

To do so, we can use the following formula in Excel:

Using these values for the predictor variables, the multiple linear regression model predicts that the value for y will be **29.22561**.

**Step 4: Use the Model to Predict Several New Values**

If we’d like to use the multiple linear regression model to predict the response value for several new observations, we can simply make absolute cell references to the regression coefficients:

**Additional Resources**

How to Perform Simple Linear Regression in Excel

How to Perform Multiple Linear Regression in Excel

How to Perform Polynomial Regression in Excel

How to Create a Residual Plot in Excel