At present time, industrial accidents statistics are used as the basic data of the policy to prevent industrial accidents and the plan to applicate the industrial accident insurance. But this statistical data is not sufficient for the effective safety management because it is the expression of the itemized distribution and the frequency for the whole cases. This study tried to correlational analysis for each causes by defining investigational items as their accident parameters. The correlational analysis, between the unsafe action and status and their relational causes, was performed to analyze the occurrence causes of industrial accident. And to assume the severity of accident, the correlativity and independency between causes and direct causes which are defined hospital days subordinate parameter were analyzed. In addition, this study expressed numerically the effectiveness of subordinate parameters depended on the level of independent parameter by presenting the predictive model between dependent parameter and independent parameter, which have the categorical parameter, through the Logit analysis method.