Physically-based landslide susceptibility analysis has been extensively employed to predict the likelihood of landslides owing to its remarkable predictive capability. However, due to an insufficiently comprehensive analysis of the vegetation-disaster connection, this approach may face limitations in its application to regions where there is significant variation in vegetation diversity and topography. An integrated model was thus proposed for predicting landslide susceptibility with the consideration of the positive and negative effects of vegetation on slope stability. However, to accurately implement the slope failure process under the influence of vegetation, it is important to have a high temporal resolution rainfall scenario for simulating the interception process of vegetation crowns on rainfall. Analysis of vegetation hydrological processes is associated with difficulties in a regional area because of limited data availability. The stochastic simulation method for extreme rainfall scenarios, adopted in this study, is known to be effective in dealing with uncertainty caused by insufficient data. The method, which comprises the Gumbel model and Bounded Random Cascade Model (BRCM), was used to overcome the difficulties in integrating the comprehensive effects of vegetation, the results of which provide refined rainfall scenarios for landslide susceptibility prediction from the perspective of the failure mechanism of vegetated slopes. The application of the proposed method for landslide susceptibility zoning was validated using a confusion matrix and ROC curve analysis in a practical case. Results showed that the method performed effectively and reliably. Furthermore, this study investigated the influence of different extreme rainfall scenarios on slope stability. Results revealed that as the return period of extreme rainfall increased from 50 to 150 years, the overall proportion of susceptible areas for different rainfall durations exhibited an upward trend. Additionally, the study found that increasing vegetation biomass had a positive impact on slope stability in the study area. The findings of this study are significant for disaster prevention and mitigation in mountainous regions, providing scientific support for risk management strategies.