This study aimed to test two hypotheses: (i) on the Brazilian semiarid territory, the climate has greater weight as a driver of vegetation than the soil and; (ii) the arboreal Caatinga is a vegetation whose environmental attributes are similar to the Dry Forest, in terms of soil and climate attributes. We analyzed attributes of the superficial horizon of 156 standardized profiles distributed throughout the Brazilian semiarid region. Bioclimatic variables were obtained from the WorldClim platform and extracted to profiles location. The main vegetation types in the region were considered: Caatinga, arboreal Caatinga, Dry Forest and Cerrado. Variable selection was performed with hierarchical correlation dendrogram and recursive feature elimination algorithm. Linear Discriminant Analysis and Random Forest (RF) algorithm were used for modeling the edaphic and climate niche and predict the vegetation with the selected variables. Climate and soil, individually, were able to separate the vegetation, but the climate was no better predictor than the soil. Therefore, we reject the first hypothesis. However, the better prediction was attained with the combined use of soil and climate attributes. The parsimonious RF model had good performance, with Kappa 0.61±0.10 and 70.9%±7.7% accuracy. The combination of soil and climate predictors resulted in better separation of vegetation in the Brazilian semiarid region. Soil attributes are key variables in large-scale biogeographic modeling. The so-called arboreal Caatinga is distributed over a wide edaphic and climatic range, with strong similarity to the Dry Forest distribution, confirmed by the great overlap in the multivariate space, which confirms the second hypothesis. The results point towards an urgent review of the Atlantic Forest Law. The environments where the arboreal Caatinga and the Dry Forest occur are very similar, so that the former may represent a degraded phase of the Atlantic Forest, currently without the due legal protection.