Abstract
Prediction models are used for knowing the behavior of highly related complex data. The prediction of morphological structures, and especially the mandible from cranio-maxillary variables, has clinical and investigative odontological usefulness. For example, in cases of trauma, pathologies and in forensic sciences, especially when it is necessary to¬ individualize a missing person, using facial reconstruction. The aim of this paper is to predict mandibular morphology through artificial neuronal networks, using cranio-maxillary measures in posterior-anterior radiographs.