Objective To construct the risk prediction model for intracranial infection (ICI) after craniotomy in neurosurgery department by logistic regression analysis, and evaluate its effect. Methods Patients who underwent craniotomy from January 2019 to June 2021 in the neurosurgery department of a hospital were selected as research objects, according to whether ICI occurred after the operation, they were divided into case group and control group, logistic regression analysis was used to analyze the risk factors for ICI after craniotomy, the risk prediction model was constructed, and the effect was comprehensively evaluated by means of Hosmer-Lemeshow goodness-of-fit test and receiver operating characteristic (ROC) curve. Results A total of 778 patients undergoing craniotomy were included, 121 of whom had post-operative ICI, incidence was 15.55%; logistic multivariate regression analysis showed that subtentorial surgery, ventricular drainage time ≥3 days, use of gelatin sponge ≥3 pieces, bleeding volume ≥300 mL, cerebrospinal fluid leakage of incision were independent risk factors for ICI after craniotomy (all P < 0.05); the risk prediction model of ICI after craniotomy was logit(P)=5.408+0.833×(subtentorial surgery)+0.083×(ventricular drainage time)+1.059×(use gelatin sponge)+0.456×(bleeding volume)+2.821×(incision cerebrospinal fluid leakage); Hosmer-Lemeshow goodness-of-fit test showed that there was no significant difference in the predicted probability and the actual incidence of intracranial infection (P=0.768); the validation accuracy of logistic regression risk prediction model was 86.00%, the area under ROC curve was 0.847, and 95%CI was 0.814-0.878. Conclusion Subtentorial operation, ventricular drainage time ≥3 days, use of gelatin sponge ≥3 pieces, bleeding volumn ≥300 mL and cerebrospinal fluid leakage of incision are independent risk factors for ICI after neurosurgical craniotomy, the risk prediction model constructed by logistic regression analysis has a good prediction effect on post-operative ICI.