Owing to their much-reduced carbon footprint and lower embodied energy, compared to conventional Portland Cement (OPC-based) Concrete mixes, Alkali Activated Concrete (AAC) mixes represent a pivotal advancement towards achieving sustainability goals. The fracture properties were investigated using Three-Point Bending Tests (3-PBT) under the mode I failure mechanism. This study utilises Taguchi analysis to analyse and optimise Self-Compacting Alkali-Activated Concrete (SAAC), focusing mainly on its flexural strength and fracture characteristics. An L-16 orthogonal array of experiments with three input parameters − replacement of Blast Furnace Slag (BFS) with Fly ash (FA) (0 %, 30 %, 40 %, and 50 %), Steel Fibers (SF) volume content (0 %, 0.25 %, 0.5 % and 0.75 %) and Notch to Depth (a0/d) ratio (0.2,0.3,0.4 and 0.5), at four levels each, was adopted. The Work of Fracture Method (WFM) and Double K Fracture Criterion (DKFC) were utilised to determine the Fracture Energy (GF) and fracture toughness, respectively. The results obtained from all the sixteen mixes showed that the F0-S0.75-N0.5 mix demonstrated better values in several parameters, such as flexural strength of 7.82 MPa,KICini of 0.928 MPa√m, KICuns of 6.99 MPa√m and KICini/ KICuns of 0.133. A maximum GF of 2350 N/m was obtained with F50-S0.75-N0.2 mix. However, all the inferior values of these parameters were observed with F50-S0-N0.5 mix, which recorded a flexural strength of 4.90 MPa, KICini of 0.612 MPa√m,KICuns of 1.16 MPa√m, KICini/ KICuns of 0.528 and GF of 125 N/m. Through Taguchi analysis, the optimal combination for flexural strength was identified as FA 0 %, SF 0.75 %, and a0/d 0.5 and for both Initial Fracture Toughness (KICini) and Unstable Fracture Toughness (KICuns) at FA 0 %, SF 0.75 % and a0/d 0.4. For both the ratio of initial to unstable fracture toughness (KICini/ KICuns) and fracture energy (GF), the optimum combination was FA 0 %, SF 0.75 % and a0/d 0.2. Furthermore, the results indicate that FA significantly influences KICini, while SF predominantly affects all other parameters. The predictive performance of the regression equations demonstrates good agreement with experimental outcomes.