Determining variabilities of soil properties is important for ecological modelling, environmental predictions, precise agriculture, and management of natural resources. This study was aimed to examine Inverse distance weight (IDW) to predict the spatial variability of Exchangeable Sodium Percentage (ESP), Calcium Carbonate Percentage (% CaCO3) soil pH, Electrical conductivity and % Gypsum . The study area selected for this work consists of Ayn Hizam, Qaryat- Batth and Taknis. Data for 220 randomly distributed representing soil profiles were encoded in spreadsheets, 198 of them were used for predicting the spatial variability in the GIS environment for ESP, % CaCO3, soil pH, Electrical conductivity and % Gypsum. The rest of Data (i.e. 22 representative soil profiles) were utilized to evaluate the maps produced using Kriging or IDW methods. The results showed that using IDW method was trustable because the values of RMSE and R2 for all the IDW maps were within the acceptable range. The study suggested adopting the Geostatistical methods for studying spatial prediction for different soil proprieties. In addition, the study recommended updating soil data for the study area.