Hantai District, Hanzhong City, Shaanxi Province was used as the study area in order to further explore ensemble model in landslide susceptibility. 40 landslides were delineated through relevant data and field investigation. Logistic model tree (LMT) and rotation forest (ROF) model were constructed by selecting 12 impact factors from geology, hydrology, and human engineering activities, then landslide susceptibility maps were generated respectively. ROC curve was used to verify and compare the model accuracy. The results showed that landslides in study area are most affected by topography, plan curvature and type of rock and soil. The prediction rates of the two models are both high, and the results of classification are basically consistent with the distribution trend of the historical landslide locations. The accuracy of training set and prediction rate of validation set of ROF model were 77.4% and 93.1%, respectively, which were higher than that of LMT model (75.5% and 84.0%). ROF model has a frequency ratio of 6.52, which is higher than LMT model (2.07), indicating that ROF model is more sensitive to landslide susceptibility in study area, and the prediction results have high reliability. The results of landslide susceptibility zoning in the ROF model can provide a basis for disaster prevention and land planning in the future.