The paper aims to propose a Monte Carlo seasonal exponential smoothing and job capacity model based on order forecasting and production line balance, to solve the problem of unreasonable staffing caused by the uncertainty of the order arrival of e-commerce enterprises and the particularity of warehousing operations. The probabilistic statistical method was used to solve the problem of incomplete ordering. The smoothing coefficient in the seasonal exponential smoothing method was optimized by this method to modify the prediction model. And then the software-Crystal ball was used to optimize the production line scheduling. The analysis of the example showed that when this method was used for prediction, the accuracy was improved by 45%. The predicted value was used for the sorting operation capacity arrangement and the optimal number of people and the distribution of working hours were determined. It can provide accurate forecasting information for e-commerce companies, as well as reasonable staffing solutions to improve business efficiency.