Objective To explore the independent risk factors for nosocomial infection in elderly patients with acute ischemic stroke (AIS), and to construct a visualized nomogram prediction model, providing objective basis for the early identification of high-risk populations and the formulation of stratified prevention and control strategies in clinical practice. Methods A total of 131 elderly patients with AIS admitted to Nanyang Second People’s Hospital from January 2024 to June 2025 were retrospectively enrolled. Nosocomial infection was determined according to the WS/T 857-2025 standard, and patients were divided into an infection group (n＝ 42) and a non-infection group (n＝89). The general information, underlying disease status, stroke characteristics (National Institutes of Health Stroke Scale (NIHSS) score, infarction volume), invasive operation history and hospital-related indicators of the two groups of patients were collected. After screening potential associated variables through single-factor analysis, multiple-factor Logistic regression was used to determine the independent risk factors for nosocomial infection. Based on the regression results, a nomogram prediction model was constructed. The discrimination and calibration of the model were evaluated using the receiver operator characteristic (ROC) curve and the Hosmer-Lemeshow test, and internal validation was conducted using the Bootstrap method. Results The incidence of nosocomial infection among the 131 enrolled patients was 32.06% (42/131), with respiratory tract infection (59.52%) and urinary tract infection (26.19%) being the predominant sites. The results of the multivariate Logistic regression analysis showed that impaired consciousness (OR＝3.504), dysphagia (OR＝4.129), indwelling urinary catheter (OR＝4.419), and prolonged length of hospital stay (OR＝1.324) were all independent risk factors for nosocomial infection in elderly AIS patients (all P < 0.05). The area under the curve (AUC) of ROC curve of the nomogram model constructed based on the above variables was 0.854 (95%CI: 0.789 - 0.919), the Hosmer- Lemeshow test χ2＝7.251, P＝0.510. After Bootstrap calibration, the AUC of the model still reached 0.841. Conclusions Impaired consciousness, dysphagia, indwelling urinary catheter, and prolonged length of hospital stay are all independent risk factors for nosocomial infection in elderly patients with AIS. The nomogram prediction model constructed in this study has stable performance and can provide a reference for clinical implementation of individualized risk assessment and stratified prevention and control.