Predictive Modeling for Customer Churn

As a data scientist at a telecom company, I need to build a predictive model to identify customers at risk of churning within the next 3 months. I have access to historical customer data, including usage patterns, payment history, and demographic information. Develop a statistical model that uses clustering techniques, decision trees, and machine learning algorithms to predict customer churn probability. Please provide a detailed explanation of your methods and a step-by-step guide to implementing the model using Python libraries such as Scikit-learn and Pandas.