Session description Predictive models are transforming value-based care by identifying patients at risk, informing clinician decision-making, and helping organizations manage financial risk. However, the gap between model output and clinical adoption remains wide. This session offers a roadmap for building predictive models that clinicians trust, actuaries can validate, and organizations can use to drive both clinical impact and financial performance. We'll explore case studies where predictive modeling enabled better intervention design, reduced avoidable utilization, and improved financial forecasting. We'll also share practical frameworks for improving model transparency and usability, which is crucial to ensure that models inform action, not just analytics. Learning objectives By the end of this session, participants will be able to: - Identify ways predictive modeling supports clinical intervention and improves patient outcomes. - Understand how predictive models are used to manage financial risk in value-based care arrangements. - Apply principles of clinical trust-building to model development and deployment. - Evaluate modeling strategies that balance technical rigor with real-world impact.