This project focuses on predicting customer churn in the telecom industry using machine learning. The dataset contains multi-year subscriber records across regions, service providers, and network technologies. Multiple ML models were trained and evaluated, using different Machine learning models. The model helps identify critical churn patterns such as high-risk circles, providers, and technologies