The ability to diagnose and monitor field scale salinity condition has been considerably refined and improved through the use of electromagnetic induction survey instruments. The EMI 400 prediction technique was made using salinity survey data from three separated fields. Three frequencies were used during collecting the measurements (14 KHz, 15 KHz, and 16 KHz). The zigzag orientation was used for measurements distribution. Simple correlation and multiple liner regression models were combined with ordinary kriging to construct field average salinity estimates to produce spatial salinity map. From the multi regression analysis, the EMI 400 reading values at frequency 14KHz justified 74.7% and 89.5% of the variations that existed in the measured EC values for plot 1 and 2, respectively. While the EMI 400 reading values at frequency 15KHz, justified 68.1% of these variation for plot 3.There is a general spectral pattern similarity between EMI 400 readings maps and the estimated ECe maps. This confirms that EMI 400 readings are appropriate for reconnaissance survey to provide a priori spatial information about salinity; allowing allocation of the most and least saline areas. The study shows the usefulness of using electromagnetic sensor (EMI 400) to assess, predict and map soil salinity at field scale.