The study area is found in Gindeberet district of West Shewa zone in Oromia Regional State of Ethiopia.This area is highly susceptible to active surface processes due to the presence of rugged morphology with steep scarps, sharp ridges, cliffs, deep gorges and valleys. This study aimed to identify and evaluate the causative factors and to prepare the landslide susceptibility maps (LSMs) of the study area. Two bivariate statistical models i.e. Information value(IV) and the Frequency ratio(FR), were used. First, active, reactivated and passive landslides and scarps were identified using Google Earth image interpretation and extensive field survey for landslide inventory. A total of 580 landslide were randomly selected into two datasets in which (80%)460 landslides were used for modeling and (20%)116 landslidesfor validation. conditioning factors (slope, aspect, curvature, distance from stream, distance from lineaments, lithology, rainfall and land use) were combined with a training landslide dataset in a ArcGIS to generate LSMs which weredivided into verylow, low, moderate, high and veryhigh susceptibility zones. LSMs for IV and FR models were validated using the Area under(ROC) curve showing a success rate of 0.836 and 0.835 respectively and a predictive rate of 0.817 and 0.818 respectively wich showed a good performance of both models. The resulting LSMs can be used for land use planning and management.