Rain water harvesting is an appropriate option for storing surface runoff for subsequent uses during periods with limited access to water. The most important step in the application of rainwater harvesting systems (RWH) is the site selection suitable areas. Therefore, by identifying suitable sites for this purpose, time and cost will be saved . In this research, multivariate regression model and GIS were used to site selection in situ (RWH) in Tajare watershed. For this purpose, layers such as crown cover, litter, rock and stones, soil, curve number, rainfall, slope and depth of field as independent variable and infiltration were considered as the dependent variable. Then, according to the maps, their values were calculated in average for each of the 27 sub-basins. Also, to investigate the relationship between these variables and weighting, each of the effective layers of multi-variable regression was used by the stepwise method The results showed that the linear multivariate regression model with an explanation coefficient of 0.993 was able to estimate the penetration factor values well In terms of grade of importance, the curve number variables with a coefficient of -2.433, depth of soil with a coefficient of 0.3488, and rubble and gravel percent with a coefficient of 0.057, were the most important, and other factors were not significant. Comparison of the map from the site selection of multivariate regression in this research with some recommended criteria of various research studies showed that the predicted classes with good in the central parts of the basin and very good in the upstream areas of the basin which in the eastern and southeastern part of the basin fit have a good overlap with the recommended areas with these criteria.