Hip fracture surgery is a common procedure with significant implications for patient care and healthcare resource management. Predicting length of stay (LOS) after hip fracture surgery can help optimize patient care and resource allocation. In addition, the emergence of COVID-19 has raised concerns about its impact on hospital outcomes. The aim of this study was to develop a predictive model for LOS after hip fracture surgery that incorporates demographic, clinical, and COVID-19-related factors. We conducted a monocentric retrospective study using administrative data of hip fracture surgery patients during 2022. Multiple linear regression with a hierarchical approach was used to successively analyze three models. Model 1 included basic demographic variables, while model 2 included severity of illness (comorbidities). Model 3 included COVID-19 positivity as a new factor. A total of 340 patients were included in the study, 74.7% of whom were female with a mean age of 81.9 years. Mean LOS was 10.5 days. Model 1 showed low significance and poor fit. Model 2 showed improved performance and highlighted the influence of comorbidities on LOS. Model 3 significantly improved predictive ability, with COVID-19 positivity contributing to explained variability in LOS (R-squared: 0.131; adjusted R-squared: 0.121; F-statistic: 27.919). Our study developed a predictive model for LOS after hip fracture surgery, taking into account demographic, clinical, and COVID-19-related factors. The results have implications for identifying patients at higher risk for prolonged hospitalization, optimizing patient care, and resource allocation. Healthcare providers can use this model to improve patient outcomes and potentially reduce healthcare costs associated with prolonged hospitalization. Further research is needed to validate the findings and explore the impact of COVID-19 on the recovery of hip fracture patients in different settings.