In conclusion, we developed an integrated data-driven and expert augmentation approach for synthetic route evaluation that aligns closely with chemists' expert assessments. Our scoring system, underpinned by expert augmentation, offers a robust evaluation criterion for guiding route selection in chemical synthesis. Additionally, this expert-augmented approach holds promise for other applications, such as optimizing AI tools in healthcare or refining autonomous systems, where human expertise is essential to address data sparsity and bias.