In the quest of renewable energy technologies, solar photoreforming emerges as one of the affordable yet challenging process for converting biomass into hydrogen, hydrocarbon fuels, and chemicals. This review highlights the state‐of‐the‐art photoreforming, elucidating its underlying mechanisms for the conversion of dissipated polymers into H2 and valuable chemicals. Biomass feedstocks such as carbohydrates, agricultural residues, glycopolymers, food wastes, and waste plastics are evaluated based on their chemical composition, energy content, and sustainability aspects, exploring the selection of appropriate bio‐renewable resources, considering their abundance, availability, and potential for hydrogen production. The impact of diverse process parameters on photoreforming efficiency is explored, encompassing factors like reaction temperature, pH, catalyst loading, reactor design, solvent effect, and light intensity across various sacrificial substrates. The discussion also considers their correlation with hydrogen production rate, selectivity, and energy efficiency. This review buckles on the design and synthesis of functional photocatalysts for biomass‐derived feedstock, highlighting their photocatalytic (PC) properties in biomass reforming processes and related feedstock into valuable chemicals and biofuel. The review also delves into potential pathways for future advancements including artificial intelligence (AI) and machine learning (ML), alongside addressing the challenges and insightful perspectives within this evolving field of future green energy.