This project aims to study the predictive analysis, which is a method of analysis in Machine Learning. Many companies like Ola, Uber etc uses Artificial 
Intelligence and machine learning technologies to find the solution of accurate fare prediction problem. The work underwent comparative analysis of algorithms 
like Linear Regression and Random Forest Regression, which are useful for prediction modeling to get the most accurate value. This research will be helpful to those,
 who are involved in fare forecasting. In previous era, the fare was only dependent on distance, but with the enhancement in technologies the cab’s fare is dependent 
on a lot of factors like time,pickup and dropoff locations, number of passengers, number of hours etc. The study is based on Supervised learning whose one application
 is prediction, in machine learning.