Predictive analytics uses data from the past to predict future outcomes. It involves collecting good quality data, applying statistical and machine learning techniques to identify patterns, and creating models based on reliable assumptions. Common predictive analytics applications include recommending products to customers, forecasting sales, determining digital ad placements, and predicting stock prices. The key is developing models based on attributes that still apply over time and checking assumptions are still valid, as using outdated assumptions can lead to incorrect predictions and even economic failure.