To explore the influencing factors of anti-tuberculosis drug-induced liver injury (ATB-DILI) in hospitalized tuberculosis patients, and to establish a risk prediction model of Nomogram. A retrospective study was conducted on 5 681 tuberculosis patients admitted to Guiyang public health treatment center from January 2017 to June 2021, including 3 342 males and 2 339 females. The inpatients with ATB-DILI were selected as the case group (214 cases) and the non-ATB-DILI patients as the control group (5 427 cases). The baseline characteristics, tuberculosis condition, behavior and disease-related data of the patients were retrospectively analyzed, and the influencing factors were screened by chi-square test and multivariate logistic regression, based on which the Nomogram model was constructed and verified. The decision curve was used to evaluate the clinical application value of the model. In this study, 3.8%(214/5 681) patients developed ATB-DILI. Multivariate logistic regression analysis showed that extrapulmonary tuberculosis (=1.876, <0.001), malnutrition (=4.411, <0.001), complicated with underlying liver disease (=4.961, <0.001) and intermittent use of hepatoprotective drugs (=2.137=0.007) were independent risk factors for ATB-DILI, while whole-course use of hepatoprotective drugs (=0.292, <0.001) was protective factor. The Nomogram model was constructed based on the above five related factors. The area under the receiver operating characteristic (ROC) curve was 0.749 (95%:0.713-0.786), the sensitivity was 0.640, and the specificity was 0.752, respectively. The Bootstrap method was used for internal repeated sampling for 1 000 times, the average absolute error was 0.003, the correction curve and the ideal curve were basically fitted, and the predicted values were in good agreement with the actual values. Hosmer-lemeshow test showed that the model had a good degree of fit (χ=3.068, =0.381). The decision curve showed that the Nomogram model had certain clinical practicability in the high risk threshold range (0.10-0.68). The Nomogram model for risk predicting ATB-DILI among inpatients with tuberculosis in this study has good predictability, consistency and clinical practicability, and can provide a basis for clinical prevention and control of ATB-DILI and individualized treatment in the process of anti-tuberculosis treatment.