<p>Casting technology is a fundamental and irreplaceable method in advanced manufacturing. The design and optimization of casting processes are crucial for producing high-performance, complex metal components. Transitioning from traditional process design based on "experience + experiment" to an integrated, intelligent approach is essential for achieving precise control over microstructure and properties. This paper provides a comprehensive and systematic review of intelligent casting process design and optimization for the first time. First, it explores process design methods based on casting simulation and integrated computational materials engineering (ICME). It then examines the application of machine learning (ML) in process design, highlighting its efficiency and existing challenges, along with the development of integrated intelligent design platforms. Finally, future research directions are discussed to drive further advancements and sustainable development in intelligent casting design and optimization.</p>