This thesis investigates how religious holidays affect the chance for ceasefire success. It does so while engaging in the topic of explanation and prediction, with combined methods consisting of regression analysis and forecasting using random forests. The theoretical framework argues that religious holidays impose higher audience costs for violence on leaders, increasing the chance for successful agreements. This would manifest as ceasefires connected to religious holidays being more successful than those that are not. The findings from the regression analysis find no support for the hypothesis, and rather indicate that conflict intensity, ceasefire duration, as well as monitoring and verification and enforcement mechanisms better explain the apparent variation in success. The forecasting indicates a minor difference in predictive power between the model including holiday and religiosity and the one excluding them, as well as minor effects of the independent variables on ceasefire success from partial dependence plots. These findings do not oppose the rejection of the hypothesis but rather indicate the need for an increased prevalence of forecasting methods within peace and conflict research and robustness tests using other definitions of success.