A wise cash forecasting method based on a dynamic weighted combination model is proposed in this study, to precisely predict the daily cash consumption of ATM equipments so as to make a better decision for daily cash transfer management. Different from single-algorithm prediction used in the past, with analyzing characteristics of banking business, transaction flow, and equipment, etc., an intelligent algorithm based on a dynamic weighted combination model that combining 4 single machine learning models, is proposed and implemented in this study. This algorithm provides a more intelligent, more precise, and more efficient forecasting method for the management of bank cash consumption, effectively reduces the total amount of cash inventory and the rate of cash return, and improves the utilization rate of cash. This method has been used in Guangdong, Chongqing, Jiangxi, Shanxi, Beijing, and other areas with sound results.