Many shallow landslides are triggered by heavy rainfall. Previous studies of landslide modeling have been hampered by the scarcity of rain gauges to adequately depict the spatial variability of rainfall conditions triggering landslides. This study simulates the efficiency of the critical rainfall model for landslide prediction in a mountainous watershed with inputs of different rainfall estimates associated with a typhoon (tropical cyclone) event. Doppler radar data at a spatial resolution of 1 km and measurements from six gauging stations provide the sources for rainfall estimates. Inverse distance weighted, splines, and kriging are the interpolation methods for gauged rainfall estimates. A comparison of the simulation outputs shows that the model using radar rainfall estimates has a better performance than those using gauged rainfall estimates in predicting both landslides and stable areas. In light of the results, this paper also discusses the validity of the critical rainfall model for landslides in relation to its rainfall input and steady-state hydrological assumption.