This paper reports on the design of an optimal knowledge base for integrated Artificial Neural Network (ANN) and Expert Systems (ES). In this system, an orthogonal plan is used to define an optimal set of examples to be taken from a problem domain. Then holistic judgments of experts on these examples will provide a training set for an ANN to serve as an initial knowledge base for the integrated system. Any counter-examples in generalization over the new cases will be added to the training set to retrain the network in order to enlarge its initial knowledge base.