Introduction: Coronary artery disease (CAD) is one of the leading causes of global mortality, and its early detection can help reduce complications and improve patients' quality of life. Among several predisposing factors, inflammation and inflammatory genes play a significant role in the disease's pathogenesis. MicroRNAs (miRNAs), small non-coding molecules that regulate gene expression, have emerged as promising biomarkers for early CAD detection due to their stability in biological fluids, specific expression patterns, and crucial role in regulating inflammation-related genes in early pathogenesis. Moreover, innovations like machine learning integration enhance diagnostic accuracy, with significant clinical implications for patient management.

Materials and Methods: This review was conducted to study the role of miRNAs in CAD pathogenesis, assess their diagnostic potential, and identify clinical challenges and opportunities. Studies from 2019 to 2025 were reviewed using databases like PubMed and Web of Science with keywords "microRNA," "CAD," "early detection," and "biomarker." The findings can be applied to develop practical diagnostic tools.

Results: The review of articles indicates that miRNAs such as miR-21, miR-208a, and miR-133a have been extensively studied, while new candidates like miR-499 and miR-126 show high diagnostic potential and can be practically applied for early detection.

Conclusion: The innovative integration of multi-miRNA panels with machine learning algorithms not only boosts diagnostic accuracy but also promises personalized predictive tools in clinical settings. This study proposes a framework for non-invasive diagnostic tools, emphasizing innovations like multi-miRNA panels and machine learning integration. The results suggest that standardizing methods and validating findings in larger populations are key to success. These findings hold clinical importance by potentially improving patient management and reducing CAD-related mortality.