Introduction A Decision Tree is a flowchart-like structure in which each internal node represents a condition on an attribute with binary outputs(e.g. Head or Tail in a coin flip), it has node and branches, where the node represents the condition and branches represents the outcome. These decision trees are very helpful in predicting the binary outcomes of an action. These decision trees can be used not only for building predictive models but also in Imputation, Encoding etc. In the Case of Variable Encoding, the variables are encoded based on the predictions of the Decision Tree. A single feature & the target variable is used to fit a decision tree, then the values of original datasets are replaced with the predictions from the Decision tree.