Modeling of complex dynamic systems, for which establishing mathematical models is very complicated, requires new and modern methodologies that will exploit the existing expert knowledge, human experience and historical data. On one hand, Fuzzy Cognitive Maps (FCMs) are very suitable, simple, and powerful tools for simulation and analysis of these kinds of dynamic systems. On the other hand, human experts are subjective and can handle only relatively simple FCMs; therefore, there is a need of developing novel approaches for an automated generation of FCMs using historical data. Although, many novel learning algorithms are published in literature, there is no software existing that especially focuses on a learning method for FCMs. In order to fill this gap, and to help researchers and developers in social sciences, medicine and engineering, a graphical user interface (GUI) is designed. Since the interest of developing software or a GUI in Matlab is increasing within the last years, the proposed FCM-GUI is developed using Matlab. In this study, a new optimization algorithm, which is called Big Bang-Big Crunch (BB-BC), is proposed for an automated generation of FCMs from data. Two real-world examples; namely an ERM maintenance risk model and a synthetic model generated by the proposed FCI-GUI are used to emphasize the effectiveness and usefulness of the proposed methodology. The results of the studied examples show the efficiency of the developed FCM-GUI for design, simulation and learning of FCMs.