Yucheng District of Ya'an City in China, the so-called rainy city of Sichuan province, is chosen as the research target for this paper. Based on rich practical data, the paper describes in-depth research into various factors affecting the occurrence of landslides, conducts an overall analysis on the relationship between the time-space distribution of landslides and rainfall, and explores the method to determine the threshold of precipitation which induces regional landsliding. It also establishes in preliminary terms the system for precipitation-induced landslide forecast and early warning. Based on the inverse modelling carried out in the research area in 2004, all approaches described are practical, feasible and can provide a scientific basis for active disaster mitigation and prevention. The paper advocates the CF logic regression model to address the consolidation of different data layers during the critical evaluation through GIS-based statistical analysis model and the determination of data layer superposition weight. By combining the certainty coefficient (CF) and logic regression model (Binary Logistic) and with the assistance of SPSS statistical analysis software, the factor selection, heterogeneity data consolidation and the data layer superposition weight are solved and the precision and efficiency of landslide susceptibility zoning are improved. Quantitative investigation has been conducted on the expressed rainfall precipitation for the rainfall threshold that induces regional landsliding, based on the logical regression coefficient. Expressions considering both the rainfall intensity and rainfall threshold have been established. Regional precipitation-induced landslide forecast and early warning system is established, based on the landslide risk zoning and landslide rainfall threshold.