The study area is one of the landslide prone areas due to its geographical location and natural and geological features. In this study, we have used statistical modeling to select the most important landslide factor in the region and also the extent of involvement of each factor in landslides in Latian Basin; The information layers used include: lithology, land use, precipitation, altitude, slope, slope direction, vegetation, fault, road, dam lake and river; More than 120 landslides and landslides were identified and landslide distribution maps have been prepared for the area. To determine the relative importance and effect of effective factors and factors in landslide risk zoning, first the degree of correlation of factors was calculated by Pearson correlation coefficient, then the weighting or scoring method was used and by two-variable statistical modeling of landslides, two factors were considered. Then, by weighting or scoring method and by bivariate statistical modeling with the obtained weights, the factors were examined together to obtain the degree of involvement of these factors in landslides. Finally, we have prepared zoning maps. By field visit of the basin after zoning and recording the location of new landslides that have occurred in the basin, we have matched the location of these recorded landslides with zoned maps, the most overlap in the very sensitive and highly sensitive classes is the information map. Achieved, the results show that according to the total quality index, the information value method is more efficient than the information value method for the Latian basin.