Git is a distributed version control system that enables developers to seamlessly collaborate on a project. It tracks changes made to the source code and implements various features upon which the modern software development process is built. Reliance on Git in the software development process requires comprehensive testing to ensure its functionalities operate reliably and consistently across projects. We show how active automata learning can enable model-based testing of Git. Active automata learning automatically derives models of the input-output behavior of Git and learned models provide a foundation for model-based testing. In addition, learned models could be used to ensure compatibility between Git versions.