We develop a predictive analytics solution to estimate Customer Lifetime Value using supervised machine learning techniques. After preparing feature variables and calculating key metrics like recency and frequency, we partition the data into training and testing sets to ensure model generalizability. We implement a linear regression model using scikit-learn to quantify the relationship between customer behavior and long-term revenue. By evaluating performance metrics such as Mean Squared Error and visualizing actual versus predicted values, we provide the business with a framework to segment customers and formulate data-driven marketing strategies that maximize return on investment.