The present paper aims to test performances of semi-automatic tools for mesh-to-mesh processing while assessing sex and ancestry in documented human crania. The studied sample of 80 human crania, which originated in two documented Brazilian collections (Sao Paulo, Brazil) was digitized using photogrammetry and laser scanning. 3D cranial morphology was quantified by computing inter-mesh dissimilarity measures using in-house freeware FIDENTIS Analyst (www.fidentis.com). Numerical outputs were further processed using Discriminant Function Analysis and Canonical Variant Analysis in order to classify models into sex and ancestry groups. In addition, cranial morphology was described by a set of 37 landmarks, processed by a Procrustes analysis and confronted with the inter-mesh comparison. Patterns of sexual dimorphism and ancestral group-specific variation were interpreted using average meshes and further emphasized by employing advanced visualization graphics. The mesh-to-mesh processing was capable to detect shape differences related to sex and ancestry. The highest accuracy levels for sex determination were obtained for meshes representing the facial skeleton and the supraorbital region. For both, analysis correctly assigned 82.5% of the crania. Ancestry-related differences were manifested primarily in the global cranial features (observed accuracy rates reaching 63%). The advanced visualization tools provided a highly informative insight into sexual dimorphism and ancestry-related variation. While in the current state the technique cannot be considered suitable for being implemented into the everyday forensic practice, the extent of automatization proved to be perspective, especially for assessing skeletal features that cannot be properly quantified using discrete variables.