This chapter focuses on risk assessment and management as core components of a proactive Well Integrity Management System (WIMS). It highlights how structured risk evaluation enables operators to identify potential hazards, prioritize threats, and implement mitigation strategies across the well lifecycle. The chapter introduces key hazard identification methods such as HAZID and HAZOP, along with structured tools like Failure Modes, Effects, and Criticality Analysis (FMECA) for assessing failure scenarios at a component level. Risk matrices are presented as practical tools for ranking hazards based on likelihood and consequence, while Bow-Tie analysis offers a visual approach for mapping threats, barriers, and outcomes. The chapter also explores the role of Quantitative Risk Assessment (QRA), including Fault Tree and Event Tree Analyses, to provide numerical insights into the likelihood and severity of well integrity failures. It emphasizes the application of risk assessment results for design optimization, inspection planning, remediation prioritization, and demonstrating compliance with ALARP principles. Finally, the chapter introduces emerging data-driven and machine learning approaches that leverage historical well data and real-time monitoring to dynamically predict failure risks and improve decision-making. Through these methodologies, this chapter underscores the importance of integrating both traditional and advanced risk management techniques to enhance well integrity, safety, and sustainability.