ABSTRACT: Landslides are one of the most destructive natural hazards which frequently occur after earthquakesin our country and in the world. From engineering point of view, prediction of landsliding before itsoccurence has a great importance to mitigate the landslide related damages, and determination oflandslide prone areas by the methods, based on probability, has spread out both in our country and in theworld in the last two decades. In this study, a comparison of the most common landslide susceptibilitymapping methods, namely bivariate, multivariate statistical and heuristic methods, were carried out. Forthis purpose, Ayvalık (Balıkesir) and its near vicinity were selected as study area, and in total 45landslides were mapped. Morphologic, geologic and land-use data were produced in GeographicalInformation Systems (GIS) by using available topographical and relevant thematic maps. In the area,slope gradient and aspect, lithology, weathering conditions of the rocks, stream power index (SPI),topographical wetness index (TWI), distance from drainage, density of structural features, land-cover andvegetation cover density were considered as the parameters causing the landslides. All of the parameterswere standardized in a common scale by using fuzzy membership functions. Then, the contribution of eachof these parameters for the landslide occurrence were investigated by likelihood ratio, logistic regressionand analytical hierarchy methods, and the weight values of the parameters were calculated. Consideringthe weight values determined by each method, landslide susceptibility maps were produced, and theperformances of the produced maps were tested by comparing landslide locations using Area UnderCurvature (AUC) approach. Based on this, the AUC values were determined to be 0.76, 0.77 and 0.89 forlikelihood ratio, logistic regression and analytical hierarchy models, respectively. Accorrding to theseresults, analytical hierarcy model was considered to be the best landslide susceptibility method for thestudy area.