Objective To explore the factors affecting the prognosis of patients with carbapenem-resistant Enterobacterales (CRE) healthcare-associated infection (HAI) after neurosurgical procedure, construct and validate a nomogram prediction model. Methods Data of patients with CRE infection after neurosurgical procedure in a tertiary hospital in Shanghai from 2018 to 2023 were collected, patients were divided into death group and survival group based on prognosis. LASSO regression and multivariate COX regression analysis were adopted to screen independent risk factors and construct nomogram prediction model. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were drawn based on Bootstrap internal validation method to evaluate the effectiveness of the model. Results A total of 241 patients were included in analysis, with 221 in the survival group and 20 in the death group. The LASSO and COX regression analysis results showed that gender, length of hospital stay >30 days, decreased monocyte percentage (MONO%), and elevated creatinine (Cr) were independent risk factors for death in patients with CRE HAI after neurosurgical procedure. The nomogram prediction model for risk of death in CRE patients after neurosurgical procedure was established based on these findings. The model validation results showed that at the 30th day, the calibration curve approached the ideal curve, the area under the ROC curve was 0.981 (95%CI: 0.947-1.000), the DCA curve showed that when the threshold of risk of death exceeded 8.36%, there was a higher net benefit value. Conclusion The nomogram prediction model for prognosis during hospitalization in CRE HAI patients after neurosurgical procedure constructed based on LASSO-COX regression analysis has good goodness of fit and predictive performance, which can provide reference for early screening of high-risk patients and implementation of intervention measures in clinical practice.