Abstract: Antibody drug conjugates (ADC) have emerged as a cutting-edge technology in anti-tumor treatment, making significant strides in recent years. ADC couple a highly active small molecule toxin payload to highly specific antibodies through a linker, enabling precise targeting of tumor cells while reducing systemic toxicity, thereby expanding the therapeutic window. However, due to the complexity of ADC molecule design, its efficacy and safety are influenced by various factors. Model-informed drug development (MIDD) is a powerful tool that utilizes various mathematical models for modeling and simulation to conduct quantitative analysis, guiding drug development and decision-making. By integrating multi-faceted data and information using mathematical models, it is possible to gain insights into the complex mechanisms, pharmacokinetics, and pharmacodynamics of ADC, providing unique perspectives for optimizing ADC development processes and clinical translation decisions. This review will introduce the basic concepts of MIDD and ADC and discuss application cases of MIDD in different stages of ADC development, aiming to provide beneficial references for the advancement of ADC.