Objective To analyze, fit, and forecast the data of hepatitis C report of China by the autoregressive integrated moving average model (ARIMA). Methods The data of hepatitis C report of China from January, 2004 to July, 2012 was differentiated to obtain smoothness and analysis, fitting, and forecasting were conducted by the seasonal ARIMA model. Results The incidence of Hepatitis C showed an increasing trend from January, 2004 to July, 2012 and has obvious periodic changes on a basis of one year. The smoothing test, differentiation, and model identification and diagnosis were conducted based on the data of Hepatitis C report and the obtained optimal model was seasonal series of ARIMA (1,1,1)×(1,1,1)12. The residual test of this model showed a white noise sequence, fitting the data in the 95% confidence interval. Based on the cases of hepatitis C from July, 2012 to December, 2014, it could be predicted that the incidence of hepatitis C increased continuously and showed an obvious trend of periodical fluctuation. Conclusion The seasonal series ARIMA model of time series can simulate and predict the tendency of incidence of hepatitis C in China and can provide reference for the prevention and control of the epidemic.