Most of the applied methods to determine the Exchangeable Sodium Percentage (ESP) and Sodium Adsorption Ratio (SAR) are time consuming and sometimes expensive, especially in calcareous soils, due to the dissolving of CaCO3 and Mg CO3 during the chemical analysis and then erroneously driving to an increase of Cation Exchange Capacity (CEC) value. To work around these problems, many researchers have developed Pedotransfer Functions (PTFS ) as an attempt to estimate these parameters from easy-to-obtain some soil characteristics such as Electrical Conductivity (EC). In this work, linear regression models using the EC as a predictor for estimating the ESP and SAR were developed with high recommended determination coefficients. In order to validate these models, they were applied to estimate ESP and SAR from EC for 26 soil samples collected from AlJabal Al-Akhdar in the eastern region of libya. The paired samples t-test analysis of these compared samples showed no significant difference between the laboratory measurements and those estimated by the regression models.