<p>The increasing demand for sustainable construction motivated the research on cement alternatives. Thus, this study investigated the performance of Wollastonite, as a partial replacement of cement in concrete. The different mechanical properties were tested at 7, 14, 28 days for mixes with varying Wollastonite content (5–25%). From the test results, it was identified that on replacement with 10% and 15% Wollastonite, the compressive, tensile and flexural strength were found to be optimum, respectively. Moreover, finite element modelling (FEM) simulations (single and dual tyres) were performed in ABAQUS, and it was observed that Wollastonite-blended concrete showed lower stresses and deflections compared to conventional concrete. The obtained results were further tested for multi-layer perceptrons (MLPs) and adaptive neuro-fuzzy inference systems (ANFIS) models to confirm the optimal Wollastonite replacement percentage. ANFIS indicated a greater R² value (&gt; 0.89), as compared to MLP (R² &gt; 0.6), providing consistent and supportive evidence for the experimentally observed optimal replacement range. Therefore, the present data-driven approach can be adopted for sustainable concrete mix design, where the application of Wollastonite not only enhances the mechanical properties but also serves as a cost-effective, eco-friendly substitute for cement. However, it is essential to articulate that the results obtained from machine learning methodologies serve to provide supportive evidence rather than constituting definitive proof of the hypotheses being tested.</p>