Burn scars represent a significant clinical challenge, owing to their morphological complexity and their functional and aesthetic impact on the patient. Traditionally, the assessment of such scars relies on subjective scales, which are prone to inter-observer variability. This study proposes an innovative approach that integrates colorimetric analysis with artificial intelligence models to provide an objective and reproducible assessment of burn scars. To this end, two novel colorimetric indices—the Erythema Index (EI) and the Vascularity Index (VI)—were introduced. These indices, when combined with machine learning algorithms, enable the automation of scar analysis, yielding promising results in terms of accuracy and reliability.