Background: Osteotomies during rhinoplasty are usually based on surgeon's proprioception to determine the number, energy, and trajectory of impacts. Objective: The first objective was to detect the occurrence of fractures. The second objective was to determine when the thicker frontal bone was encountered by the osteotome. Materials and Methods: An instrumented hammer was used to measure the impact force during lateral osteotomies on nine human anatomic specimens. A prediction algorithm was developed using machine learning techniques, to detect the occurrence of fractures, and the proximity of the osteotome to the frontal bone. Results: The algorithm was able to predict the occurrence of fractures and the proximity to the frontal bone with a prediction rate of 83%, 91%, and 93% when allowing for an error of 0, 1, and 2 impacts, respectively. The location of the osteotome in the frontal bone was predicted with an error of 7.7%. Conclusion: An osteotomy hammer measuring the impact force when performing lateral osteotomies can predict the occurrence of fractures and the proximity to the frontal bone, providing the surgeon with instant feedback.