<p>Rainfall infiltration analysis has a significant effect on landslide assessment. The investigation of the input parameters of infiltration analysis is limited on the large scale. Therefore, an infiltration analysis using Monte Carlo simulation was proposed to deal with the uncertainty of the input parameters in the infiltration computation process. A sensitivity analysis was performed to assess the contribution of each parameter. Then, the proposed model was applied to Saka town, Hiroshima Prefecture, Japan. The landslide probability map was also computed to validate the proposed model using inventory from 2018 landslides. The results show that both curvature and porosity are the most sensitive, followed by hydraulic conductivity and slope. These parameters were stochastically included when calculating the saturated depth on the large scale. The saturated depth map with and without uncertainty consideration was compared. The results illustrate that the maximum saturated depth at each rainfall duration considering uncertainty is less than without uncertainty consideration. The area under the receiver operating characteristic curve (AUC) was used to validate the landslide probability map. The result indicates the proposed model is fair, with an AUC of 73.8%, while AUC is 70.7% for model without uncertainty consideration. The proposed approach may be utilized to analyze rainfall infiltration-induced landslides in the future.</p>