<p>Plant-derived indigoid dyes, such as indigo and indirubin, exhibit remarkable optical and chemical properties that have fascinated researchers for centuries. In recent years, computational chemistry has become an indispensable tool for unraveling the molecular intricacies underlying their color, stability, and spectroscopic behavior. This review provides a critical synthesis of how diverse computational methods—including Density Functional Theory (DFT), Time-Dependent DFT, Molecular Dynamics (MD), and hybrid QM/MM approaches—have been applied to indigoids. These techniques enable the prediction and rationalization of UV–Vis spectra, vibrational modes, and NMR shifts, offering insight into structure–property relationships and environmental influences such as pH, solvent polarity, and substrate binding. Special attention is given to excited-state processes like ESIPT and internal conversion, which underpin indigo’s exceptional photostability. Additionally, computational strategies for modeling dye aggregation, tautomerism, and degradation pathways are discussed, demonstrating the synergy between theoretical predictions and experimental observations. The review highlights the role of computational tools not only in heritage science and dye chemistry but also in guiding the design of novel derivatives and sustainable applications. Future directions point toward integrating machine learning, advanced multiscale simulations, and enhanced benchmarking to further refine our understanding and expand the utility of indigoid systems in both traditional and emerging technological contexts.</p> Graphical abstract <p></p>