Abstract: Al-Si alloy is characterized by excellent strength, toughness, and wear resistance, making it widely utilized in aerospace, automotive manufacturing, and electronics. Machine learning, a prominent branch of artificial intelligence, aims to enable computer systems to learn from data and autonomously enhance their performance; it has found extensive applications in materials science. In recent years, machine learning has significantly contributed to the investigation of the mechanical properties of Al-Si alloys. The current state of research on the application of machine learning in inverse design, mechanical property prediction, and its integration with the CALPHAD method for the design of Al-Si alloys were reviewed. The existing challenges in the domain were identified and the viable solutions and future research directions were proposed