Landslides usually occur in Taiwan and result in property losses and casualties due to the large hilly and mountainous area with high steepness and heavy rainfall caused by typhoons. The occurrence of landslide is a very complex and highly nonlinear phenomenon. The support vector machine, which performs precisely and efficiently in nonlinear problems without too many assumptions, is firstly employed herein to develop a landslide susceptibility model for the Kao-Ping River basin in southern Taiwan. The model performance is checked using the confusion matrix and the area under the receiver operating characteristic curve (AUC). The validation results show that the true positive rate, the accuracy, and the AUC are 92.9%, 71.3% and 0.792, respectively. This indicates that the proposed model can provide reasonable landslide prediction. The proposed model can also provide the landslide susceptibility map which will be a helpful tool for landslide warning.