Panoramic radiography is a routine technology used to diagnose oral and maxillofacial pathology; it has the advantages of low cost, high speed, and safety because of the reduced dose and exposure time to radiation. Third molars are responsible for benign or malignant tumors that can result in neurological problems, diminish the resistance to fractures owing to their position in the bone and frequently generate infectious problems. The appropriate planning and classification allow patients to be treated safely and help reduce waiting lists. We used panoramic radiography and machine learning to identify the inclination, depth, and available space of third molars to support diagnosis and surgical treatment. In experiments, our approach identified third molars with 100% accuracy The molars were classified as per the Winter and Pell-Gregory classification schemes having high accuracies of >80%. The contribution of this work adds value to the imaging diagnosis, allowing an estimation of the disinclusion time of third molars to support the surgical management of the operating room.