Uses sensor data, log histories, and environmental metrics to train models (e.g., survival analysis, anomaly detection) that predict equipment degradation or failures before they occur. Governance includes validating model accuracy, defining alert thresholds, integrating alerts into maintenance workflows, and periodically retraining models as equipment ages or usage patterns change. Audit trails track predictions, maintenance actions, and outcomes for continuous improvement.