This comprehensive literature review delves into the application of Scheffe's Simplex Lattice Model for optimizing cement concrete mixtures, with a particular emphasis on its impact on material properties and sustainability. The review meticulously outlines the principles, his-torical context, and advantages of Scheffe's model, providing a nuanced understanding of its significance. Comparative analyses with traditional and alternative optimization techniques in concrete mix design illuminate the distinct advantages of statistical methods, especially Scheffe's model. The review critically examines the challenges and limitations associated with applying Scheffe's model, addressing issues related to the complexity of concrete mixtures and computational demands. Potential avenues for improvement are explored, suggesting refine-ments to handle non-linearity, incorporate advanced optimization algorithms, and streamline computational requirements. Additionally, the review highlights emerging trends in statistical modeling for concrete mixture optimization, such as the integration of machine learning and data-driven approaches, signaling the evolving landscape of concrete technology. In conclu-sion, the literature underscores Scheffe's Simplex Lattice Model as a valuable and versatile tool with far-reaching implications for the advancement of concrete mixture design methodolo-gies. The call to action encourages ongoing research and development to refine the model, explore emerging trends, and address practical challenges, positioning Scheffe's model as a cornerstone in the pursuit of sustainable, resilient, and high-performance concrete materials.