Lateral radiography is one of the most important records for patients’ evaluation in orthodontics and cephalometric analysis is fundamental to conduct correct diagnosis and treatment plan. This analysis includes both linear and angular measurements that quantitatively describe cranial and intermaxillary relationships. In order to obtain such measurements, anatomical landmarks are used. These reference points can be found on the soft tissue profile and on hard tissues such as teeth and skeletal contour. It is important to be extremely precise in the identification of these landmarks to compute correct measurements: even the slightest discrepancy could result in wrong values leading to different and possibly erroneous treatment plan. The automatic computerized identification of such anatomical landmarks on lateral cephalograms would greatly simplify this important step in the diagnostic process. Our aim is to apply artificial intelligence techniques for the automatic detection of these landmarks, with the final objective of developing a software, THERE (auTomatic HElpeR for cEphalometry), which exploits a predictive model that analyses teleradiographs, returns the coordinates of the anatomical landmarks, and automatically calculates the measurements necessary for diagnosis. This short paper describes the system interface and the first results obtained towards the training of the model(s) for landmarks prediction.