The research aims to produce, model, and optimise the mechanical properties of novel composite material through a structured multidisciplinary approach. The primary objective is to combine materials science, mechanical engineering, and statistical concepts to ensure Design for Manufacturability (DFM) from the industrial perspective. More specifically, the article is intended to determine the optimal mixture components and predictive model of Al-Si alloy with Al2O3 by accommodating multi-responses that enable DFM. The study adopted ASTM standards to prepare and test the novel composite material. Additionally, the Mixture Design of Experiment (DOE) approach was used to design the experimentation and subsequent analysis. In addition, microstructural images, Cox Response Trace plot, and Response Optimiser plot are effectively utilised to draw robust inferences. For multi-response modelling and optimisation, the composite material’s mechanical properties, like impact strength, hardness, density, and tensile strength, are considered. The study determines that innovative composite material will yield better results when Al-Alloy is 94.65 wt% and Al2O3 is 5.35 wt% from a multi-responses perspective. Further, it provides predictive models with a high level of predictability. Besides, the research shows that novel composite material has better mechanical properties from a practical perspective. The article not only provides the mechanical properties of a new class of material but also shows the effective utilisation of material science and statistical concepts to develop the novel material in a structured manner. This composite material can be used as a replacement for various parts of automobiles and aircraft. Additionally, researchers can use the article’s modelling and optimisation approach as a paradigm to create durable composite materials.