Internationalization started to be seen as an opportunity for many companies. This is one of the most crucial growth strategies for companies. Internationalization can be defined as a corporative strategy for growing through foreign markets. It can enhance the product lifetime, and improve productivity and business efficiency. However, there is no general model for a successful international company. Therefore, the success of an internationalization procedure must be estimated based on different variables, such as the status, strategy, and market characteristics of the company. In this paper, we try to build a model for evaluating the internationalization success of a company based on existing past data by using Fuzzy Kernel Robust C-Means. The results are very encouraging and show that Fuzzy Kernel Robust C-Means can be a useful tool in this sector. We found that Fuzzy Kernel Robust C-Means achieved 85.40% accuracy rate with RBF kernel, 70% data training, and σ = 0.05.