Abstract: To identify the marker metabolites of pepper chicken contaminated by Salmonella, liquid chromatography-mass spectrometry (LC-MS) was used to analyze the metabolite profiles of pepper chicken contaminated by Salmonella and control group, and random forest regression analysis and stepwise multiple linear regression were used to identify the key marker metabolites of pepper chicken contaminated by Salmonella. In the process of pollution degree, 1475 different metabolites were identified and analyzed, then 864 and 611 metabolites were identified in positive and negative ion mode respectively. The top 20 kinds of positive and negative ion patterns were selected as potential marker metabolites by random forest regression analysis. Receiver operating characteris curve (ROC) analysis showed that the biomarkers of amidinotaurine, taurocholic acid, 5b-carp cholesteryl sulfate and uridine -5'- monophosphate identified by random forest regression analysis showed a strong correlation with Salmonella-contaminated pepper chicken, in which the content of uridine -5'- monophosphate was significantly increased, which had a strong ability to distinguish Salmonella-contaminated pepper chicken from fresh pepper chicken. It could be used as a marker metabolite after Salmonella contamination of pepper chicken. The findings of this study could provide a theoretical basis for developing an innovative method to identify and detect food-borne pollution caused by Salmonella.