<p>3D concrete printing continues to expand rapidly, yet the diversification of materials and printing systems has made it difficult to compare results across studies and to identify generalizable mix design strategies. This article presents the first comprehensive, data-driven synthesis of 1149 unique 3D printable concrete (3DPC) mix designs extracted from more than 330 published sources. All mixes were standardized to a consistent basis, enabling direct comparison of binder composition, aggregate content, water demand, and admixture usage across the literature. To identify representative formulation types, <i>K</i>-means clustering was applied to the full dataset. Five statistically distinct clusters were obtained, capturing systematic differences in cement loading, cement substitution, paste fraction, and aggregate proportions. Examination of cluster centroids and representative mixes highlights recurring approaches to balancing printability, strength development, and material efficiency, and reveals where mix designs across the field tend to converge or diverge. This work provides the most extensive quantitative overview to date of 3DPC material strategies. By establishing underlying patterns and representative mix types, the analysis offers a robust foundation for mix design benchmarking, methodological harmonization, and future development of performance-based specifications for structural 3D printing.</p>