Metabolic engineering, the optimization of cellular metabolism for the production of valuable compounds, relies heavily on computational modeling and analysis to guide design strategies and predict metabolic outcomes. MATLAB, a powerful computational platform widely used in engineering and scientific research, offers a versatile toolkit for metabolic engineering applications. This review provides an overview of the diverse applications of MATLAB in metabolic engineering, spanning from metabolic network reconstruction and simulation to strain optimization and pathway design. We discuss the key functionalities of MATLAB relevant to metabolic engineering, including systems biology toolboxes, optimization algorithms, and dynamic modeling capabilities. Additionally, we highlight case studies and examples demonstrating the utility of MATLAB in addressing challenges such as metabolic flux analysis, pathway analysis, and strain design. Moreover, we explore emerging trends in MATLAB-based metabolic engineering, such as genome-scale modeling and machine learning approaches, and their potential impact on biotechnology and industrial applications. By synthesizing knowledge from computational biology, bioprocess engineering, and MATLAB programming, this review aims to provide researchers and practitioners with insights into the application of MATLAB in advancing metabolic engineering research and applications.