Rheumatoid arthritis (RA) is a chronic autoimmune disease character-ized by inflammation and joint destruction, leading to significant disability and reduced quality of life. Current treatment options for RA have limitations, highlighting the need for novel therapeu-tic approaches. In this study, we employed network pharmacology methods to identify potential bioactive compounds from Persea Americana (avocado) for the treatment of RA. We collected information on the phytoconstituents of avocados from the IMPPAT database and used Data Warrior software to filter out 64 plant constituents based on ADMET criteria. Target genes associated with avocado compounds were identified using the Bindingdb web server, resulting in 209 genes from Persea Americana. Protein-protein interaction (PPI) network analysis was performed using Cytoscape software to identify key genes and pro-teins involved in RA. Protein-drug interactions were analyzed, and ten avocado constituents with high binding affinity were identified. Our network pharmacology analysis revealed that avocado constituents, particularly Luteolin, have the potential to be developed as novel therapeutics for RA. The PPI network analysis identified key genes and proteins associated with RA, providing insights into the molecular mechanisms of the disease. The high binding affinity observed between Luteolin and PTGS2, a protein involved in joint inflammation, suggests its potential effectiveness in mitigating RA-related inflammation. Our study highlights the potential of avocado constituents, particularly Luteolin, as promising therapeutics for the treatment of rheumatoid arthritis (RA). Through network pharma-cology analysis, we identified key target genes and proteins associated with RA, shedding light on the underlying molecular mechanisms of the disease.