Predictive modeling works by analyzing past data such as customer purchase history, engagement metrics, and demographic information. Machine learning algorithms are then used to identify patterns and relationships within the data. These patterns are used to predict future customer actions, such as the likelihood of opening an email, clicking on a link, or making a purchase. The predictive models are continually refined as more data becomes available, improving their accuracy over time.