Predictive modeling in data science is used to forecast future outcomes based on historical data. It employs statistical techniques and machine learning algorithms to create models that identify patterns and relationships within datasets. By analyzing trends, predictive modeling enables organizations to make data-driven decisions, optimize operations, and enhance customer experiences. Applications include predicting customer behavior, identifying potential risks in finance, and forecasting demand in supply chain management. This proactive approach supports strategic planning and helps in mitigating uncertainty.