Abstract: The assessment of landslide susceptibility is an important means to guide the preliminary early warning and forecast of regional landslide. In order to improve the accuracy of landslide susceptibility evaluation in county area, random forest model (RF) and frequency ratio model (FR) were used as the basic models, and RF-FR was established to evaluate landslide susceptibility combined with the advantages of the two models. In Lueyang county domain for the study area, selection of elevation, slope direction, slope, formation, surface roughness, the distance from the fault, curvature and the distance from the road, terrain humidity index, the distance from the river, a database of 14 factors such as rainfall, by adopting the method of Spearman correlation analysis of each factor, eliminate topographic relief degree of three high correlation of evaluation factors, and evaluate the relative point density (LRPD) based on landslide factor analysis. The results show that:①there is a negative correlation between the distance between landslide disaster points and linear factors, that is, the closer the distance is, the more disaster points are. ②The prediction rates of FR, RF and RF-FR models are 84.3%, 90. 1% and 95.0%, respectively. Compared with FR and RF models, the prediction accuracy of RF-FR model is 10.7% and 4.9% higher than that of FR and RF models. ③The proportion of landslide disaster points in high and extremely high-risk areas of 4RFmurFR model is 15.89% and 5.29% higher than that of FR and RF model, respectively.