In this paper, we conducted a case study on the relationship between the soil geochemical components and the occurrence of soil salinization in the west of Jilin Province in China employing the GIS technologies and statistical analysis. We found that (i) the geochemical components are closely correlated with soil salinization and (ii) the selected eighteen geochemical components, S, K, Be, Cu, MgO, CaO, Na2O, Ph, Eh, Ba, Sb, F, Tl, Sr, Th, Pb, Se, Ge, were characterized with hierarchy and could be restructured into ten determinant factors after a CLUSTER and FACTOR analyses. In addition, this paper developed a binary logistic model with the occurrence or without occurrence of soil salinization as the dependent variable while the soil geochemical components as independent variables, which can be employed to diagnose and assess the current or potential soil salinization. A surface interpolation was conducted to validate and check the robustness of the models. We found that the classical statistical methods combining the surface interpolation constituted an effective and efficient framework to identify the relationship between soil geochemical components and the salinization and make an assessment on the soil salinization.