Geostatistics provides descriptive tools to characterize the spatial distribution of soil attributes. Kriging techniques rely on the spatial dependence between observations to predict attribute values at un-sampled locations. Cokriging on the other hand, utilizes the spatial correlation between two variables to map the primary one, which is under-sampled, using information content of the secondary variable. Collocated cokriging is used when the primary and the secondary variables are sampled at the same location. The present study aimed at applying collocated cokriging to map topsoil sodicity (primary variable) measured in 28 samples, using the information content of topsoil salinity (secondary variable) measured in 134 samples. Topsoil sodicity (SAR) ranged between 3.65 and 28.85, whereas topsoil salinity (EC) varied from 0.36 to 12.24 dS/m. The correlation coefficient, r, between the two variables is 0.98, which satisfies the most important criteria for carrying out cokriging. The fitted semivariograms for both variables are Gaussian, and the cross-semivariogram between the two variables is also Gaussian. The cokriged spatial distribution of topsoil sodicity was mapped and compared to kriged SAR. The cokriging results were cross-validated and the standard error of estimation was matched to that of kriging. The study showed the superiority of cokriging upon kriging as a spatial mapping method, especially if the primary variable is under-sampled.