Rheumatoid arthritis (RA) is a systemic chronic autoimmune disease characterized by joint damage and systemic involvement. Despite advancements in understanding RA, early diagnosis and effective treatment remain challenging due to the complex pathogenesis and limited specificity of current biomarkers. Metabolomics, offers a promising approach for identifying new biomarkers to assess treatment responsiveness in RA. A systematic review was conducted to identify key metabolites and metabolic pathways that may reveal responsiveness to different drug therapy strategies (methotrexate, TNF, and IL-6 inhibitors) in RA treatment. The systematic search was conducted in PubMed and Google Scholar in accordance with PRISMA recommendations. The risk of bias and the quality of the final selected studies were assessed in duplicate using the Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) tool and using the QUADOMICS tool. Eighteen studies were eligible for data extraction. Metabolomic studies revealed distinct profiles for responders and non-responders to different RA treatments. For methotrexate therapy, key metabolites included for example: homocysteine, glycerol-3-phosphate, and diphosphoglyceric acid. TNF inhibitor response was associated mainly with changes in carbohydrate derivatives and amino acids. IL-6 inhibitor studies identified metabolites such as N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic acid as potential predictors of response. Across studies, metabolomic profiles demonstrated high sensitivity and specificity in distinguishing responders from non-responders. These studies collectively highlight alterations in TCA cycle metabolites, amino acids, nucleotide metabolism, and lipid profiles, among others. This review supports the identification of better treatment strategies choosing methotrexate, TNF, or IL-6 inhibitors as therapeutic interventions based on metabolomics profiling.