Abstract: Maximum a posteriori Bayesian (MAPB) method has attracted more and more attention in individualized dosing. Through a combination of prior population pharmacokinetics (PPK) characteristics of the target population and the results of therapeutic drug monitoring (TDM), the individual PK parameters of patients can be accurately estimated, and thus the individualized pharmacotherapeutic strategies based on PK/PD principle can be formulated. MAPB is used to optimize dose individualization of various therapeutic areas such as anti-infective drugs, immunosuppressants, anticoagulants, and antineoplastics, helping to increase the proportion of patients reaching the target therapeutic window, avoid adverse drug reactions, shorten length of hospital stay and improve clinical outcomes. So far, several MAPB-based clinical decision support systems have been developed to guide individualized dosing. This review aims to present the concepts of MAPB, clarify its process, illustrate its application in individualized dosing in various therapeutic areas, and introduce some MAPB-based clinical decision support systems, in an attempt to provide reference for further research and dose individualization.