Background <p>Meningitis is a significant complication following nasal trans-sphenoidal surgery for pituitary tumor resection. Meningitis increases hospital stays and costs, posing a burden to both patients and healthcare systems. This study aimed to develop a perioperative predictive model for meningitis based on key factors, such as the operation duration, tumor diameter, and intraoperative cerebrospinal fluid (CSF) leakage.</p> Methods <p>A retrospective analysis was conducted on patients undergoing pituitary tumor resection via the nasal trans-sphenoidal approach. Predictive factors for meningitis, including operation duration, tumor diameter, and intraoperative CSF leakage, were analyzed. The model's predictive efficacy was evaluated using the collected data.</p> Results <p>Meningitis occurred in 8.7% of cases (35/401). Intraoperative CSF leakage, observed in 24.2% of cases, significantly increased the risk of infection. The tumor diameter was also linked to higher infection rates. The constructed model demonstrated good predictive performance, allowing for early risk identification.</p> Conclusions <p>This study developed a predictive model for Meningitis after pituitary tumor resection using the operation duration, tumor diameter, and CSF leakage. The model provides healthcare professionals with an effective tool to assess infection risk and implement timely intervention strategies to improve patient outcomes.</p> Graphical Abstract <p></p>