Abstract: The development of Geographic Information System (GIS) technology provides a new technical method for the evaluation of landslide risk. Support Vector Machine is the hotspot of machine-learning industry research, and has been applied successfully in many areas. By taking Xianyou County as an example, a new method for landslide hazard evaluation based on GIS and Support Vector Machines (SVM) is presented in this paper. It includes the basic principles and methods of SVM, selection and quantification of landslide hazard evaluation index, foundation of SVM model and the way to realize it. According to the actual situation of the research area, the quantification method has been stipulated separately for each of six selected appraisal indexes including the elevation, the gradient, the slope, the gneiss, the rainfall and the vegetation. The system of landslide geology disaster risk appraisal has been established, the special chart of each appraisal index has been obtained by the use of the geographic information system spatial analysis function. From the results of the appraisal, the extremely high-risk danger and the high-risk danger areas are basically located in the central and northwestern parts of the study area; the secondary risk in both sides of them. This distribution result has basically reflected the present situation of geological disaster in the research area. This method can be put in practice in geology hazard investigation.