Abstract: This paper proposes a method for rule extraction based on rough set and neural network.Firstly，this paper disperses initial data set and initiative reduces condition attributes of decision-making table using rough set，then learns and forecasts data using neural network and filtrates yawp of decision-making table through deleting unclassified data，finally reduces rules using value reduction algorithm of rough set.The experiment proves that this method is quick and effective，and can remain high robustness of neural network avoiding the difficulty to extract rules from neural network compared to traditional rule extraction algorithms.