Rainfallinduced landslide disasters, which involve hydrological processes and geotechnical processes, are a complex prediction problem. In this study, a coupled hydrologicalgeotechnical model called CRESLIDE (Coupled Routing and Excess Storage and SLopeInfiltrationDistributed Equilibrium) was applied for landslides forecasting in the Yuehe River Basin. The hourly gridded precipitation data as the input of the CRESLIDE model were calculated using the inversedistance weighted interpolation method from reported values by encryption rainfall stations of China Meteorological Administration (CMA). By utilizing GIS, DEM and RS technology, the characteristic information of the test basin was extracted. The CREST distributed hydrological model was applied for simulating hydrological processes and computing the key intermediate variables as forcings of the SLIDE model to forecast rainfallinduced landslide events. We chose the Yuehe River Basin, located in the south of Shaanxi Province, as the test region for landslide forecasting. The results show that the CRESLIDE model has a generally good reliability to accurately predict occurrence of landslides (location and timing). Receiver Operating Characteristic (ROC) analysis indicated that the CRESLIDE model perform well with a high specificity (87.8%) and a reasonably good sensitivity (52.9%). Coupled hydrologicalgeotechnical framework like the CRESLIDE model is based on physical processes and has a more realistic representation of hydrological processes, so this type of model is very useful for landslide prediction and early warning. This study provides valuable information and insight for similar studies in this field.