The public healthcare system in Chile, specifically the Servicio Salud Metropolitano Sur Oriente, confronts substantial challenges resulting from lengthy waiting lists for maxillofacial surgery, affecting over one million residents. At the Centro de Referencia de Salud Hospital Providencia Cordillera, the demand for maxillofacial surgery exceeds the current capacity, with only two surgeons available to treat approximately fourteen patients per week. Despite recent efforts to augment the surgical team to four maxillofacial surgeons, the weekly patient capacity increased only to twenty-one, still insufficient to address the backlog. The primary objective of this study is to optimize the scheduling of maxillofacial surgeries to maximize the number of patients treated, taking into account varying levels of complexity and priority, without requiring additional resources. The scheduling problem was formulated as a job-shop model, and the optimization was performed using integer linear programming. The distinctiveness of this approach lies in its application to a critical public healthcare issue in a specific country and a specialized field. The model was evaluated using a sample of 500 patients, and the results indicated a significant reduction in waiting times, from fifty weeks to twenty-eight weeks - a 44% decrease - achieved solely through improved scheduling. These findings underscore the potential of operational optimization to enhance healthcare service delivery within existing resource constraints.