Abstract: In this study, the highest weighted preferences score (HWPS) and the lowest weighted preferences score (LWPS) were selected from 90 fermented pomegranate juice (FPJ) samples according to weighted preference score. Furthermore, key volatile compounds that influenced sensory preferences were predicted in 2 FPJs by using headspace solid phase micro-extraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) combined with machine learning (ML). It was found that HWPS exhibited a higher viable bacterial count, indicating that consumers preferred FPJ with higher viable bacteria count, while there was no significant differences in color parameters and antioxidant substances between 2 FPJs. A total of 33 volatile compounds were identified in 2 FPJs, respectively. The acid and alcohol levels in HWPS were 37.74% and 32.90% higher, respectively, compared to LWPS, respectively, indicating that consumers preferred products with rich volatile compounds. There were 19 key differential volatile compounds screened out by ML. Binary classification models of HWPS and LWPS were established by random forest (RF) and adaptive boosting (AdaBoost) algorithms, and RF algorithm had higher prediction precision and accuracy. According to Shapley Additive exPlanations (SHAP) analysis, the top 9 volatile compounds, including acetic acid, decanoic acid and isopropyl myristate, were the key volatile compounds that affected the scores of HWPS and LWPS. Among them, acetic acid and decanoic acid contributed to positive sensory preferences, while isopropyl myristate had negative sensory effects. KEGG analysis showed that pyruvate metabolism and sulfur metabolism were the main metabolic pathways contributed to formation of volatile compounds. This study used ML combined with SHAP analysis to predict key volatile compounds that influenced sensory preferences, which built a theoretical foundation for using artificial intelligence to aid development of FPJs with typical fermentation flavor and in line with consumer sensory preferences the food industry.