<p>Tea blending is a delicate craft that demands extensive experience and a deep understanding of ingredient combinations. Initially aimed at ensuring consistent tea qualities to meet consumer preferences, blending has since evolved to add value, enhance profitability, and diversify tea offerings. The subjective nature of blending, relying only on the tea blender’s decisions, poses challenges in maintaining consistency, reducing operational costs, and expediting the selection of optimal blends. As tea blending is a multi-faceted optimisation procedure, manual handling struggles to address multiple factors simultaneously. Traditional methods for identifying blend compositions involve costly chemical analyses. Therefore, modern technologies, like artificial intelligence, optimisation algorithms, and advanced analytics, have been integrated to boost accuracy, closely match target tea properties, accelerate performance, and uphold uniformity. Currently, a comprehensive review of tea blending is unavailable. This review explores the blending process, its challenges, and the technological advancements in optimisation and composition identification. It also introduces a new classification for blending methods, delves into research gaps, and suggests ways forward for enhancing the blending process within the tea industry.</p>