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Predictive models, which includes forecasting models, are used to study all types of conflict and political violence, including civil wars, international conflict, terrorism, genocide, and protests. These models are defined as those where the researcher explicitly values predictive performance when building and analyzing the model. This is different from inferential models, where the researcher values the accurate operationalization of a theory, and experimental or quasi-experimental designs where the focus is on the estimation of a causal effect. Researchers employ preditive models to guide policy, to assess the importance of variables, to test and compare theories, and for the development of research methods. In addition to these practical applications, there are more fundamental arguments, rooted in the philosophy of science, as to why these models should be used to advance conflict research. Their use has led to numerous substantive findings. For example, while inferential models largely support the democratic peace hypothesis, predictive models have shown mixed results and have been used to refine the scope of the argument. Among the more robust findings are the presence of nonlinear relationships and the importance of dependencies in all types of conflict data. These findings have implications for how researchers model conflict processes. As predictive models become more common and more integrated into the study of conflict, it is important that researchers understand their underlying components to use them appropriately.

UN peacekeeping serves as the foremost international tool for conflict intervention and peace management. Since the Cold War, these efforts have almost exclusively targeted conflicts within, rather than between, states. Where traditional peacekeeping missions sought to separate combatants and monitor peace processes across state borders, modern peacekeeping in civil wars involves a range of tasks from intervening directly in active conflicts to rebuilding political institutions and societies after the fighting ends. To accommodate this substantial change, peacekeeping operations have grown in number, size, and scope of mandate. The increasing presence and changing nature of peacekeeping has sparked great interest in understanding when and how peacekeeping is used and how effective it is in delivering and sustaining peace. Significant advances in peacekeeping data collection have allowed for a more rigorous investigation of the phenomenon, including differentiation in the objectives, tasks, and structure of a mission as well as disaggregation of the activities and impact of peacekeepers’ presence across time and space. Researchers are particularly interested in understanding the adaption of peacekeeping to the unique challenges of the civil war setting, such as intervention in active conflicts, the greater involvement and victimization of civilians, the reintegration of rebel fighters into society, and the establishment of durable political, economic, and social institutions after the fighting ends. Additional inquiries consider why the UN deploys peacekeeping to some wars and not others, how and why operations differ from one another, and how the presence of and variation across missions impacts conflict countries before and after the fighting has stopped.