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Among the casualties, 1 870 000 individuals with HIV co-infections contributed to 6.7% of the total fatalities, accounting TB as the second most lethal infectious disease following COVID-19. In the quest to identify biomarkers for disease progression and anti-TB therapy, microRNAs (miRNAs) have gained attention due to their precise regulatory role in gene expression in disease stages and their ability to distinguish latent and active TB, enabling the development of early TB prognostic signatures. miRNAs are stable in biological fluids and therefore will be useful for non-invasive and broad sample collection. However, their inherent lack of specificity and experimental variations may lead to false-positive outcomes. These limitations can be overcome by integrating standard protocols with machine learning, presenting a novel tool for TB diagnostics and therapeutics. This review summarizes, discusses and highlights the potential of miRNAs as a biomarker, particularly their differential expression at disease stages. 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