Modern CI/CD Pipelines generate vast amounts of build, test, and deployment data- making it challenging to detect issues before they impact production. In this session, we explore how AI and ML can transform your CI/CD process by predicting failures before they occur. You'll learn how to collect and process pipeline data(logs, test outcomes, resource metrics) to train models that detect subtle patterns indicative of future failures. This talk covers practical strategies for feature engineering, model integration using popular open source tools, and real-world case studies that demonstrate reduced downtime and optimised testing. Attendees will leave with a clear, actionable roadmap for embedding predictive analytics into their pipelines to drive proactive, resilient software delivery