Predictive analytics is one of the most powerful applications of AI in Big Data processing. It involves using historical data to predict future outcomes, trends, and behaviors. AI models, particularly those based on supervised learning algorithms like regression, decision trees, and neural networks, are trained to recognize patterns in past data and apply this knowledge to new data. Time series analysis and forecasting models are commonly used in industries such as finance, supply chain management, and healthcare to predict stock prices, demand fluctuations, and disease outbreaks. AI enhances predictive accuracy through ensemble methods like bagging, boosting, and stacking, which combine multiple models to improve performance and reduce errors.