Machine learning is applied in predictive analytics to uncover patterns in historical data and forecast future outcomes. By employing algorithms that learn from past data, machine learning models identify relationships and trends, making predictions based on new input. For instance, businesses use predictive analytics to anticipate customer behavior, optimize inventory, and improve marketing strategies. The process involves data collection, preprocessing, model training, and validation to ensure accuracy. As patterns evolve, machine learning models can adapt and refine their predictions, making them more valuable over time. This application enhances decision-making and drives efficiency across various industries.