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Background: Neurosurgical intensive care unit patients are at high risk for delirium. A risk prediction model could help the staff screen for patients at high risk for delirium. On the basis of this risk, preventive measures could be taken to reduce the undesired effects of delirium. Objectives: To establish a delirium prediction model for neurosurgical intensive care unit patients and to verify the sensitivity and specificity of this model. Design A prospective, observational, single‐centre study. Methods: Data were collected from a total of 310 patients admitted to the neurosurgery intensive care unit between January 2017 and February 2018. A risk factor prediction model was then created using multivariate logistic regression. Further data were collected from another 60 patients between March 2018 and June 2018 to validate the model. Results: The model consisted of six predictors, namely, cognitive dysfunction on admission, fever, hypoalbuminaemia, abnormal liver function, sedative use four or more times, and physical restraint. The area under the curve of the model was 0.80, with sensitivity and specificity of 0.68 and 0.83, respectively. Conclusions: This study established a delirium prediction model for neurosurgical intensive care unit patients, which we believe would help focused prevention of delirium in intensive care unit patients. SUMMARY STATEMENT: What is already known about this topic? Delirium is an acute medical condition commonly seen in general hospitals.There are many reasons underpinning delirium in ICU patients, and early screening and prevention constitute the first steps of delirium management.There are a limited number of studies that have addressed delirium in neurosurgical ICU patients. What this paper adds? This study established and validated a delirium prediction model on the basis of the risk factors associated with neurosurgical ICU patients. The implications of this paper: This delirium prediction model for neurosurgical ICU patients allows medical staff to adopt early interventional measures for patients at high risk for developing delirium, thereby preventing and reducing the incidence of this condition. [ABSTRACT FROM AUTHOR]