Conventional Portland cement concrete, though ubiquitous in infrastructure construction, exhibits inherent brittleness characterized by low tensile strength and limited strain capacity, typically failing catastrophically at microstrains of 100–200. The progressive deterioration of concrete structures due to cracking under service loads, thermal cycling, and dynamic forces necessitates the development of innovative cementitious composites with enhanced deformation capacity. This research investigates the development and characterization of flexible concrete incorporating Ground Granulated Blast Furnace Slag (GGBS) and Metakaolin (MK) as supplementary cementitious materials (SCMs) in an M30 grade concrete matrix, targeting a minimum flexural strain capacity in the range of 500–800 microstrains. The experimental program was designed to systematically evaluate the influence of partial cement replacement by GGBS (20%, 30%, and 40% by weight of binder) and Metakaolin (5%, 10%, and 15% by weight of binder), individually and in binary combination, on the fresh properties, mechanical strength, and flexural ductility of concrete. A total of eighteen mix proportions, including a control mix, were evaluated. Specimens were prepared and tested in accordance with applicable Indian Standards, including IS 10262:2019, IS 516:1959 (Reaffirmed 2018), IS 5816:1999, and IS 1786:2008. Test results demonstrated that optimized binary blends of 30% GGBS and 10% Metakaolin yielded compressive strengths of approximately 34.2 MPa at 28 days, meeting the M30 performance criterion while exhibiting a flexural strain capacity of 672 microstrains—well within the target range. The incorporation of SCMs refined the pore structure, enhanced the interfacial transition zone (ITZ), and promoted secondary pozzolanic reactions, collectively contributing to improved toughness and crack-arrest mechanisms. Strain energy density values were computed from load-deflection data, revealing a 58% enhancement over the control mix in optimized specimens. Results were analyzed using analysis of variance (ANOVA) and scanning electron microscopy (SEM) to correlate microstructural attributes with macroscopic behaviour.