Abstract: Hot strip coiling temperature is one of the important parameters of performance index in hot rolled strip，and its control system of highly nonlinearity.Traditional coiling temperature prediction model is difficult to get the high precision of prediction because of multi-factors.In order to satisfy the demands of high precision of the coiling temperature，a genetic-neural network method to predict coiling temperature based on data mining is put forward.To make full use of the association-analysis capability of data mining，the approximation capability of neural network and the liability to fall into the global optimum solution of genetic algorithm，a forecast model is established by using the method above.Checked with actual production data，the result indicates that the method could predict precisely the strip coiling temperature，and be used on-line afterwards.