Homogeneous charge compression ignition (HCCI) combustion is still confronted with problems in cycle-to-cycle air/fuel ratio control. Because there are no parameters that characterize air inflow in each cycle, dynamic recurrent neural network (Elman) was adopted for forecasting engine's air inflow in each cycle. Based on accurate air inflow in each cycle, accurate air/fuel ratio control is achieved in steady and transient operating conditions by oxygen sensor's closed loop control and fuel film’s compensation. The experiment results show that prediction model based on neural network and air/fuel ratio control strategy can meet the need of realtime control over HCCI operation. 