**Decision Tree**can be used for implementing regression as well as classification models, however ,**Linear Regression**can be used for regression problem only.

**Decision tree**can be used for regression, even when there is non linear relationships between the features and the output variable. However,**Linear Regression**works really nicely when there is linear relationship between features and the output variable.

**Decision tree**also work well compared to**Linear Regression**algorithms when there are missing values in the data.

**Decision tree**can be implemented without converting the categorical values to numerical , however,**Linear Regression**algorithms requires the categorical values to be converted to numerical values.