We propose a methodology for assessing the impacts of climate change on sediment disasters characterized by numerous debris flows occurring within a single catchment. In this study, we first developed a probabilistic prediction method for debris flow affected areas by integrating a generalized ordered logistic regression model —trained on the information from the Heavy rain of July, Heisei 30 — using rainfall and topographic data as explanatory variables, with probabilistic predictions of sediment production from this model, and a debris flow runout model. Next, by inputting current and future rainfall conditions influenced by climate change into this method, we probabilistically evaluated the flood and deposition distribution of debris flows under each condition. This approach enables the assessment of future changes in quantitative indicators, such as the probability of flow depth exceeding a threshold or the probability of deposition thickness surpassing a threshold.