Flow cytometry enables quantitative measurements of fluorescence in single cells. The technique was widely used for immunology to identify populations with different surface protein markers. More recently, the usage of flow cytometry has been extended to additional readouts, including intracellular proteins and fluorescent protein transgenes, and is widely utilized to study development, systems biology, microbiology, and many other fields. A common file format (FCS format, defined by International Society for Advancement of Cytometry (ISAC)) has been universally adopted, facilitating data exchange between different machines. A diverse spectrum of software packages have been developed for analysis of flow cytometry data. However, those are either 1) costly proprietary softwares, 2) open source packages with prerequisite installation of R or Python and sometimes require users to have experience in coding or 3) online tools that are limiting for analysis of large data sets. Here we present EasyFlow, an open source flow cytometry analysis GUI based on Matlab or Python, that can be installed and run locally cross-platform-ly (Windows and MacOS), without prerequisite user having previous knowledge on coding. The python version (EasyFlowQ) is also developed on a popular plotting framework (Matplotlib) and modern user interface (UI) toolkit (Qt), allowing more advanced users to customize and keep contributing to the software, as well as its tutorials. Overall, EasyFlow serves as a simple-to-use tool for inexperienced users with little coding experience to use locally, as well as a platform for advanced users to further customize for their own needs.