The study by Randahl et al. develops machine-learning models to forecast electoral violence globally, addressing its threat to the legitimacy and fairness of electoral outcomes. By analyzing economic indicators, historical violence, and political instability, the models predict violence risk for 2024-2025 with high accuracy, aiding in effective prevention strategies for at-risk elections.