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In the printer manufacturing industry, it is known that business impact is especially large because of the due date penalty or opportunity loss (including sales loss of toner cartridge and drum cartridge) when an inventory shortage occurs. Furthermore, in this industry, due to occurrence of sudden and large demand, it is not clear how to analyze demand distribution from historical sales data and how much inventory should be kept. We reviewed various literature regarding the demand forecasting method for sudden and large demand, but we were unable to find a proper method, and therefore decided to develop a new method ourselves. In this research, we propose a new demand forecasting method based on extreme value distribution. In the method proposed, we first classify historical sales data, then we estimate the parameters of the extreme value distribution, and finally forecast future demand. Additionally, we tested our method using real business data. As a result, we found that the method proposed performs better than the current method being used by businesses and can avoid inventory shortages when sudden and large demand occurs. [ABSTRACT FROM AUTHOR]