# Prediction Using Classification and Regression Trees

This example shows how to predict class labels or responses using trained classification and regression trees.

After creating a tree, you can easily predict responses for new data. Suppose `Xnew` is new data that has the same number of columns as the original data `X`. To predict the classification or regression based on the tree (`Mdl`) and the new data, enter

`Ynew = predict(Mdl,Xnew)`

For each row of data in `Xnew`, `predict` runs through the decisions in `Mdl` and gives the resulting prediction in the corresponding element of `Ynew`. For more information on classification tree prediction, see the `predict`. For regression, see `predict`.

For example, find the predicted classification of a point at the mean of the `ionosphere` data.

```load ionosphere CMdl = fitctree(X,Y); Ynew = predict(CMdl,mean(X))```
```Ynew = 1x1 cell array {'g'} ```

Find the predicted `MPG` of a point at the mean of the `carsmall` data.

```load carsmall X = [Horsepower Weight]; RMdl = fitrtree(X,MPG); Ynew = predict(RMdl,mean(X))```
```Ynew = 28.7931 ```