Introduction A Random Forest is a supervised Machine Learning model, that is built on Decision Trees. To understand how a Random Forest works, you should be familiar with Decision Trees. You can find an introduction in the separate article Decision Trees - Explained. A major disadvantage of Decision Trees is that they tend to overfit and often have difficulties to generalize to new data. Random Forests try to overcome this weakness.