BACKGROUND: Recurrent acute pancreatitis (RAP) poses significant clinical challenges, with 32.3% developing to chronic pancreatitis within 5 years. The underlying microbial factors contributing to RAP remain poorly understood. This study aims to identify blood microbial signatures associated with RAP and explore the potential microbial predictors for RAP. METHODS: In this prospective cohort, 90 acute pancreatitis patients are classified into non-recurrent acute pancreatitis (NRAP, n=68) and RAP (n=22) groups based on the number of pancreatitis episodes. Microbial composition of blood samples is analyzed using 5-region (5R) 16S rRNA gene sequencing. Key microbial taxa and functional predictions are made. A random forest model is used to assess the predictive value of microbial features for RAP. The impact of RESULTS: Linear discriminant analysis effect size (LEfSe) analysis highlights significant microbial differences, with CONCLUSIONS: This study identifies distinct clinical and microbial features associated with RAP, emphasizing the role of specific bacterial taxa in pancreatitis recurrence. The findings suggest that microbial profiling could enhance the diagnosis and management of RAP, paving the way for personalized therapeutic approaches.