The Buthidae is the most clinically important scorpion family, with over 500 species distributed worldwide. Taxonomical positions and phylogenetic relationships concerning the representative genera and species of this family have been mostly inferred based upon comparisons between morphological characters. Yet, some authors have performed such inferences by comparing some structural properties of a few selected molecules found in the venoms from these scorpions. Here, we propose a novel methodology pipeline designed to address these issues. We have analyzed the whole venoms from some species that exemplify peculiar cases in the Buthidae family (Tityus stigmurus, Tityus serrulatus, Tityus bahiensis, Leiurus quinquestriatus quinquestriatus and Leiurus quinquestriatus hebraeus), by means of a proteomic approach using a 2D-LC/MS technique. The molecules found in these venoms were clustered according to their physicochemical properties (molecular mass and hydrophobicity), by using the machine learning-based Weka software. The clusters assessment, along with the number of molecules found in a given cluster for each scorpion, which assigns for the venom and structural family complexities, respectively, was used to generate a phenetic correlation tree for positioning these species. Our results were in accordance with the classical taxonomy viewpoint, which places T. serrulatus and T. stigmurus as very close species, T. bahiensis as a less related species in the Tityus genus and L. q. quinquestriatus and L. q. hebraeus with small differences within the same species (L. quinquestriatus). Therefore, we believe that this is a well-suited method to determine venom complexities that reflect the scorpions' evolutionary history, which can be crucial to reconstruct their phylogeny through the molecular evolution of their venoms.