This paper proposes the expat assessment system for global management personnel training utilizing the data mining employing evolutionary computation. This study follows the three steps. First step is to research those overseas temporary staff by direct hearing and having them answer the questionnaires. The second step is to make the data base with the results acquired from the step one. The third step is to construct the system to assess the prospective staff's aptitude or adaptability. The system would enable to promote the efficiency of assessment and to be useful in their training. This expat assessment system is built with the decision tree of evaluation standard based on the assorting problem solving method. For designing the non-terminal nodes of the decision tree, a new method is proposed utilizing the idea of the association rules, which is a powerful method in data mining. This is done to find out direct factors related to aptitude or suitability for overseas staff. The terminal nodes of the decision tree are to be optimized by Genetic Algorithm (GA) regarding a series of terminal nodes as the individuals forming the linear structure. As a result, the significant factors are found, which are strongly related to aptitude, adaptability and likeliness to be successful overseas. This research has revealed, by applying the system in practice, actual aptitude, skills and personalities required for expats.