This study aimed to identify shared specific genes associated with rheumatoid arthritis (RA) and inflammatory bowel disease (IBD) through bioinformatic analysis and to examine the role of the gut microbiome in RA. The data were extracted from the 3 RA and 1 IBD gene expression datasets and 1 RA gut microbiome metagenomic dataset. Weighted correlation network analysis (WGCNA) and machine learnings was performed to identify candidate genes associated with RA and IBD. Differential analysis and two different machine learning algorithms were used to investigate RA’s gut microbiome characteristics. Subsequently, the shared specific genes related to the gut microbiome in RA were identified, and an interaction network was constructed utilizing the gutMGene, STITCH, and STRING databases. We identified 15 candidates shared genes through a joint analysis of the WGCNA for RA and IBD. The candidate geneCXCL10was identified as the shared hub gene by the interaction network analysis of the corresponding WGCNA module gene to each disease, andCXCL10was further identified as the shared specific gene by two machine learning algorithms. Additionally, we identified 3 RA-associated characteristic intestinal flora (Prevotella,Ruminococcus, andRuminococcus bromii) and built a network of interactions between the microbiomes, genes, and pathways. Finally, it was discovered that the geneCXCL10shared between IBD and RA was associated with the three gut microbiomes mentioned above. This study demonstrates the relationship between RA and IBD and provides a reference for research into the role of the gut microbiome in RA.