Logistic regression models seek to identify the influence of different variables/factors on a response variable of interest. These are normally used in the field of medicine as it allows verifying which factors influence the presence of certain pathologies. However, most of these models do not consider the correlation between the variables under study. In order to overcome this problem, GEE (Generalized Estimating Equations) models were developed, which consider the existing correlation in the data, resulting in a more rigorous analysis of the influence of different factors. There are different packages in R that allow analysis using GEE models, however, their use requires some prior knowledge of the R programming language. In order to fill this gap and enable any user to perform analysis through GEE models, a Shiny application called SAGA (Shiny Application for GEE Analysis) was developed. The developed web application is available for use at the following link http://geemodelapp2022.shinyapps.io/Shiny_App. The main purpose of the SAGA application is to develop and analyse GEE models using a dataset selected by the user, where it will be possible to describe all the variables of interest in the development of the model, as well as validate the same models developed through validation by ROC analysis. In addition to the results of the GEE models, shown in the application, the ROC curves of each developed model are also represented.