He, Y., DeSutter, T., Hopkins, D., Jia, X. and Wysocki, D. A. 2013. Predicting EC_eof the saturated paste extract from value of EC_1:5. Can. J. Soil Sci. 93: 585-594. Many laboratories appraise soil salinity from measurement of electrical conductivity of 1:5 soil to water extract (EC_1:5) due to its simplicity. However, the influence of salinity on plant growth is mainly based on electrical conductivity of saturated paste extract (EC_e), so it is necessary to convert EC_1:5 to EC_e in order to assess plant response. The objectives of this research were to develop models relating EC_1:5 and EC_e under four different 1:5 equilibration methods: (1) shaking, (2) shaking plus centrifuging, (3) stirring, and (4) a United States Department of Agriculture-Natural Resources Conservation Service (2011) equilibration method. One hundred soil samples, which were all derived from glacial parent materials in North Dakota, USA, were selected for this study. Non-transformed, non-transformed separated, ln-transformed, and exponential models were developed between EC_1:5 and EC_e. Non-transformed, simple linear regression models had obvious segments for all equilibration methods and the residual distributions varied. Therefore, data were separated at EC of 4 dS m^-1 and a quadratic curvilinear model was developed for relating EC_1:5 and EC_e (r² values ranged from 0.87 to 0.93) when EC_e values were less than 4 dS m^-1. Although the linear model was significant (P<0.05), soils having EC_e greater than 4 dS m^-1 had r² values less than 0.61. Across all soils, the ln-transformed model had r² values greater than 0.85, which was greater than the non-transformed or exponential models. By comparison of r², RMSE, and relative percentage difference, the separated curvilinear model that was established when salinity is less than 4 dS m^-1, and ln-transformed models were superior at predicting EC_e from EC_1:5 data compared to non-transformed and exponential models. These results indicate that across all equilibration methods EC_e can reliably be predicted from EC_1:5 data for soils from this region.