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BACKGROUND Post-stroke depression (PSD) was one of the most prevalent and serious neuropsychiatric effects after stroke. Nevertheless, the association between liver function test indices and PSD remains elusive. OBJECTIVE The aim of this study was to explore the relationship between the liver function test indices and PSD, and construct a prediction model for PSD. METHODS Patients were selected from 7 affiliated medical institutions of Chongqing Medical University from January 1, 2015 to January 1, 2021. Variables including demographic characteristics and liver function test indices were collected from the hospital electronic medical record system. Predictors were selected using univariate analysis, least absolute shrinkage and selection operator. Subsequently, multivariate logistic regression was adopted to build the prediction model. Furthermore, receiver operating characteristic curve (ROC), sensitivity, specificity, accuracy, calibration curve analysis and decision curve analysis were used to assess the performance of the prediction model. RESULTS A total of 464 PSD and 1621 stroke patients met the inclusion criteria. Six liver function test items, namely AST, ALT, TBA, TBil, TP, ALB/GLB, were closely associated with PSD, and included for the construction of the prediction model. The ROC curve was 0.751 in the training set and 0.708 in the validation set, respectively. Furthermore, the calibration curve analysis plot and decision curve analysis plot showed that the prediction model featured a moderate clinical practicability. CONCLUSIONS The prediction model constructed using these six predictors displayed a medium prediction ability, which could be used for the participating hospital units or individuals by mobile phone or computer.