In Telecom Industry customer churn is a big issue and one that impacts their revenue. When customers start to leave a service or subscription, it increases the expenditure for these companies. Businesses have found that acquiring new customers costs them nearly six times more money than retaining existing ones. Therefore, preventing customer churn becomes important when companies are trying to grow their business. The analysis of Customer Behaviour using Machine Learning techniques does provide an effective solution to the problem by predicting which customers are more likely to leave the service or subscription. Predictive analysis of customer behavior not only helps companies fix issues with their service but also helps them add new features and products so as to keep the customer engaged. The present work provides an overview of the latest works in the field of Customer Churn prediction. Our aim is to provide a simple path to make the future development of novel Churn prediction approaches easier.