Habitat modeling is an important tool to investigate the quality of the habitat for a species within a certain area, to predict species distribution and to understand the ecological processes behind it. Many species have been investigated by means of habitat modeling techniques mainly to address effective management and protection policies and cetaceans play an important role in this context. The bottlenose dolphin (Tursiops truncatus) has been investigated with habitat modeling techniques since 1997. The aim of this study was to develop a predictive model of bottlenose dolphin distribution and habitat preference in the whole area of Pelagos Sanctuary. We focused on the application of machine learning techniques (Random Forest).