In machine learning, a **decision tree** is a predictive model; that is, a mapping of observations about an item to conclusions about the item's target value. Each inner node corresponds to variable; an arc to a child represents a possible value of that variable. A leaf represents the predicted value of target variable given the values of the variables represented by the path from the root. The machine learning technique for inducing a decision tree from data is called **decision tree learning**, or (colloquially) **Decision Trees**.

It is also a mean for calcuating conditional probabilities.