Recently, the Korean government is actively promoting support and investment for climate technology innovation with the goal of becoming carbon neutral by 2050. For this reason, there is a growing interest and necessity for energy saving and efficiency improvement. As an alternative, various solutions have been proposed that introduce a Factory Energy Management System(FEMS) to achieve energy savings through partial system improvement. In the food industry, the scale of energy consumption is gradually increasing due to the rapid improvement of dietary standards. Therefore, energy saving in the food factory is important, but there is no application of the FEMS. In the case of some small factories, it is difficult to ascertain even the amount of energy consumed for actual production. In this study, the energy consumption pattern was analyzed to estimate the amount of energy saved when the FEMS is applied to a food factory. The optimal level of energy consumption for the food processing was derived by predicting the energy demand and supply required in food factories and analyzing the basic unit per product output. In addition, the energy consumption pattern was predicted through data mining to calculate the amount of energy savings, and the accuracy of the prediction model was evaluated.