In recent years, influenced by reforms of electric power system, economic transformation and upgrading, increased environmental protection efforts, frequent extreme weather events,and coronavirus pandemic, customers face problems such as declining output and difficult sales that increases the electric charge recycling risk. A regression model based on industry development trend is proposed to predict the electric charge recycling risk. Firstly, the seasonal adjustment algorithm is used to extract the trend item of the historical industry electricity sales, and then the affecting factors are comprehensively and quantitatively analyzed. On this basis, a prediction model is built to perceive the industry development trend. Using the perception result, combined with data such as user’s payment behavior and capacity change, an early-warning model for the electric charge recycling risk is built. The model objectively quantifies the risk probability of user’s electric charge recycling. Finally, the example verification result shows that the model has good predictive ability.