This paper discusses how to extract symbolic rules from trained artificial neural network (ANN) in domains involving classification using genetic algorithms (GA). Previous methods based on an exhaustive analysis of network connections and output values have already been demonstrated to be intractable in that the scale-up factor increases with the number of nodes and connections in the network. Some experiments explaining effectiveness of the presented method are given as well. This paper discusses how to extract symbolic rules from trained artificial neural network (ANN) in domains involving classification using genetic algorithms (GA). Previous methods based on an exhaustive analysis of network connections and output values ​​have already been demonstrated to be intractable in that the scale-up factor increases with the number of nodes and connections in the network. Some of the instructions explaining effectiveness of the presented method are given as well.