Remembering to perform an action in the future is called prospective memory (PM). It contains time-based prospective memory(TBPM)and event-based prospective memory (TBPM ). TBPM refers to remembering to perform an action at a specific time or after a certain amount of time has elapsed. And EBPMA refers that one must be performed when a certain event occurs. Both of these memory constitute a crucial form of memory use in our daily lives. This paper mainly introduces EBPM. PM contains two components, the prospective component and the retrospective component. Remembering that you have to do something is the prospective component, whereas remembering what you have to do and when you have to do it is considered the retrospective component. Unfortunately, if a variable affects prospective memory,we cannot determine how the variable affects each of the two different components using traditional accuracy measures. We cannot disentangle the two components clearly and then cannot explore the latent cognitive processes of prospective memory deeply in previous studies. This article presents a detailed discussion and application of a methodology by comparing with the paradigm of Cohen and others in EBPM, called Multinomial process tree (MPT) models. In these models, it is assumed that there are discrete cognitive states that participants attain with certain probabilities during task performance. These probabilities are represented as model parameters that can be estimated from observed raw data via maximum likelihood parameter estimation. The fit of the resulting model to the empirical data can be evaluated via goodness-of-fit tests.MPT model is relatively uncomplicated, do not require advanced mathematical techniques, and have certain advantages over other, more traditional methods for studying cognitive processes. Smith and Bayen first introduced the MPT model for the measurement of EBPM . The model is based on the preparatory attentional processes and memory processes (PAM) theory , which proposes that the prospective component involves processes that draw on our limited resources, and, thus, that these processes are not automatic. And now this theory is supported by many studies.. The authors explained why we appoint the modle in EBPM at first, and then introduced the modle in detail including the theoretical basis, the main content, the calculation method of the data, the validity and the application of the model. At the same time,the limitation in using the model of the problem are also discussed (the permise condition of using the MPT modle is that we should take the nofocal task to ensure that the participants in the experiment distribution of attention resource. Nonfocal tasks are those in which the PM cue is not part of the information being extracted in the service of the ongoing task. By contrast, focal tasks are those in which the ongoing task involves processing the defining features of the PM cue. In nonfocal tasks, prospective remembering is thought to require executive attentional resources to engage in extra monitoring for the cue to perform the intended action.), and the end of the article, we have a summary to full text and puts forward some opinions on future research, for example, how do we distribute the limited resources between ongoing task and PM task. Our goal in the work presented here was to develop and evaluate a formal mathematical model for the investigation of EBPM.