Elderly adults with hip fractures are particularly vulnerable to perioperative pulmonary complications (POPCs) throughout the surgical process. While most studies have focused on predicting postoperative pulmonary complications (PPCs), there has been a lack of focus on preoperative and intraoperative phases. To address this gap, this bidirectional cohort study aims to develop and validate a predictive model for POPCs across all surgical stages in elderly patients with hip fracture. This study will involve 3481 patients, with 1914 in the retrospective dataset and 1567 in the prospective dataset, and will analyse 44 perioperative risk factors. LASSO and multiple logistic regression will be used to identify key predictors, and nomogram prediction models will be constructed via the RMS packages. The accuracy and variability of the model will be assessed using receiver operating characteristic (ROC) curve analysis and calibration plots. The primary outcome measure is the incidence of pulmonary complications from hospital admission to 30 days post-surgery, and the secondary outcomes include complications such as heart failure, myocardial infarction, renal failure, deep venous thrombosis, stroke, and death within 30 days post-surgery. This study aims to construct a comprehensive model for predicting POPCs in this patient population and verify its accuracy and ability to differentiate POPCs using both internal and external data.