Businesses frequently collect massive amounts of information like surfing behavior, email activity, and other personal data. By applying statistical analysis to estimate a contact's transaction likelihood, this data can provide a significant competitive edge. Most businesses struggle with weeding out potential consumers from their audience. These consumers called leads are very beneficial for various purposes like enhancing a firm’s sales or expanding the business etc. The purpose of conducting this work is to find potential leads from existing consumers so that a company named X Education can enhance its conversion rate. Machine learning techniques are used for this work. We applied a logistic regression model to the data to convert the poor leads into hot leads. A generalized linear model was also used for getting the potential information of a lead and working on them. After applying the regression model the conversion rate was found to be increased to 70%.