Building on our understanding of how suicide emerges and for whom in the United States this occurs, we move into discussions of identification of and intervention for those at risk. The chapter begins with a brief overview of screening to identify those at risk of suicide, and the challenges in the research literature. Comprehensive risk assessments that incorporate multiple sources of information remain essential, and there is a potential role for machine learning in this process. We then summarize biologic (e.g., lithium, electroconvulsive therapy) and psychosocial (e.g., safety planning, cognitive behavioral therapy) promising practices in suicide prevention, as well as the potential role of technology (e.g., telehealth, apps) in suicide interventions. We then highlight community-based interventions (e.g., gatekeeper training, lethal means safety) and the evidence supporting them. At the societal level, state and federal efforts have focused on creating safe environments (e.g., legislation to reduce access to means) and providing economic supports that are promising. Given the complexity of suicide, we highlight the potential benefits of multimodal, multilevel intervention programs.