Flight Fare Prediction: The price of airline tickets is changed dynamically depending upon the various features of the tickets like destination, source, time, number of stops. Due to ever changing fare of airline tickets, it is hard for customers to predict the flight fare before purchasing the ticket leaving them confused whether to buy the ticket or not. This project report presents a simple approach for the predicting the flight fare using various algorithms like Random Forest regressor, decision tree regressor, K- neighbor classifier, Linear Regression. The proposed model uses the datasets of Indian Airline Companies available in the web. The experimental results show that the proposed method achieves 0.79 score on R-squared test achieved by using Random Forest Regressor. This study demonstrates the potential of using Random Forest Regression for flight fare prediction.