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To improve air safety and decrease aircraft accident closely to the lowest limit, improvements due to large amount of information acquisition and analysis about incidents or near misses which occurred in daily flights are important to reveal occurrence mechanisms of human errors. As the ASRS (Aviation Safety Reporting System in US), today we have huge data of human errors. We have to use the data not only to study lessons learned but also to continue to obtain new insights. This paper describe a new methodology to structure the relations between contribution factors to occur human errors in aircraft maintenance works using the Bayesian Network methodology. The first reason using Bayesian Network is that this methodology is graphical model representing causal relationships between contribution factors of human error. The next reason is it could calculate conditional probability of each contribution factors. By using these functions, it is possible to find leverage point to reduce human error. This study could attain contributions to eradication of aircraft accident. [ABSTRACT FROM AUTHOR]