The lack of information to assist future road projects in the Mossoró Microregion led to the proposal of this work, which is characterized as a preliminary and indirect alternative to indicate the soils for use in paving. Thus, this research applied statistical modeling techniques to estimate the AASHTO Classification and the CBR (California Bearing Ratio) of the soils of the study area. In the development of the models was used Geoprocessing, for georeferenced database composition, and statistical modeling techniques for modeling. For this purpose, it was used as explanatory variables: Pedology, Geology, Vegetation, Geomorphology, elevation, slope, aspect, illumination, curvature plane, curvature profile, flow contribution, direction, drainage length and east and north coordinates. The variables explained were the AASHTO Classification and the CBR. At the end, R² was 0.76 for CBR estimation, and 0.42 for AASHTO classification. The models indicated that the soil A-2-4 is predominant in the region. As for the CBR, it was possible to observe that more than 50% of the soils of the studied region present good capacity of application in sub-bases. In addition, the geotechnical characteristics estimated by these models allowed the elaboration of Geotechnical Maps, stratified to predict the values of CBR and AASHTO Classification. The models resulting from this research can aid in the decision-making process in paving works, minimizing the costs and the time of performing geotechnical studies, especially in the feasibility and pre-project studies phase.