This thesis describes the development of an application called FlagAFlag. The application was created for educational purposes, and allows the user to identify unknown flags in an easier way. The paper is divided into four chapters. The first part of the thesis deals with the collection of data and images necessary to complete this application. This thesis also identifies problems in data collection and possible solutions so that the data can be used properly in machine learning. The core of this application and this bachelor thesis is the creation of a model and the training that is done on carefully obtained data during the process of data collection. Using the Tensorflow framework, a flag classification model is created, and the methods and features used during training and data validation are clarified. After creating the model, the implementation in the Flutter framework is shown, and by using the Dart programming language; an application is created that allows a user to identify a flag with the help of a smartphone within arm's reach. Finally, a real-world demonstration of the application is shown using examples taken with the phone camera or loaded from the user gallery.