Objective To develop and validate a nomogram model for the differential diagnosis of tuberculous meningitis and cryptococcal meningitis in the human immunodeficiency virus （HIV）-negative population.Methods A retrospective analysis was performed for the clinical data of 292 patients with tuberculous meningitis or cryptococcal meningitis who were admitted to Department of Neurology， Xijing Hospital， and according to the time of admission， the patients were divided into training group with 240 patients and validation group with 52 patients. Univariate and multivariate logistic regression analyses were performed for the patients in the training group to screen out independent differentialfactors between the two types of meningitis. R software was used to establish a nomogram for differential diagnosis， and then the model was validated in the validation group. The receiver operating characteristic （ROC） curve and calibration curve were plotted to evaluate the model in the two groups.Results The univariate and multivariate logistic regression analyses showed thatage， pyrexia， autoimmune disease， initial pressure of cerebrospinal fluid， white blood cell count in cerebrospinal fluid， and glucose content of cerebrospinal fluid were independent differential factors for the differential diagnosis of tuberculous meningitis and cryptococcal meningitis （P<0.05）. This model had a sensitivity of 80% and a specificity of 76.47%. The nomogram model had an area under the ROC curve of 0.853 in the training group and 0.897 in the validation group， and the model showed good differentiation and calibration.Conclusions The nomogram model used for the differential diagnosis of tuberculous meningitis and cryptococcal meningitis in the non-HIV population has a certain clinical value in the early diagnosis and treatment of meningitis in primary hospitals.