General Processing Tree (GPT) model is a mathematical form of multinomial processing tree (MPT) models.This presentation will be divided into three parts.1) Mathematical and statistical properties of GPT models: The basic theory of GPT models will include an overview of the theoretical results that have been obtained in prior researches.I will emphasize some extensions.For example,I will talk about the extension of GPT models to analyze categorical data such as contingency tables.2) Computer software packages for GPT models: There are several computer software packages that have been created for analyzing GPT and MPT models.I will explore the features for the packages.The purpose of evaluating the existing packages is to see what else we can do to make the GPT/MPT tools available to researchers in other domains.3) Existing issues and challenges: To end the presentation,I will raise a few issues of GPT models,such as the issue of structure identifiably for GPT models.