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Rheumatoid arthritis (RA) is a chronic autoimmune disorder associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD) that is not fully explained by traditional risk factors. This study investigated whether a novel microRNA (hsa-miR) panel could improve cardiovascular risk prediction and stratification in RA patients. In this 8-year prospective cohort study, 235 RA patients were enrolled, of whom 148 completed follow-up. We quantified six hsa-miRs (hsa-miR-24, -146, -Let7a, -425, -451, and -155-5p) using qPCR and evaluated their predictive value for two primary endpoints: ASCVD progression (new atherosclerotic plaques and/or non-fatal cardiovascular events) and all-cause mortality using partial least squares discriminant analysis (PLS-DA), linear mixed models, and multivariate regression. During follow-up, 58 patients (39%) experienced ASCVD progression, and 35 died (ASCVD accounting for 31% of deaths). PLS-DA models indicated that baseline hsa-miR levels predicted both ASCVD progression and mortality, explaining 43% and 42% of outcome variability, respectively. Longitudinal changes in five hsa-miRs (-24, -146, -let-7a, -425, and -155-5p) also predicted ASCVD progression. Age, hypertension, and disease duration modulated hsa-miR expression levels over time. This hsa-miR panel represents a promising tool for improving cardiovascular risk prediction in RA, potentially addressing critical gaps in current stratification approaches. Following validation, it could support implementation of personalized cardiovascular risk assessment in RA clinical practice.