In this paper, a new method of combining computational mechanics and neural networks for prediction of composite beam delamination is proposed. One beam with delamination, as well as a ‘healthy’ beam with no delamination, had a four-ply symmetric carbon/epoxy composite design, were fabricated simultaneously. The delamination was assumed at different location of the beam, and then the finite element analysis was performed and the modal frequencies of the composite beam were obtained, which were used to train the neural network. The piezoelectric patch was attached to the top of the composite beam to measure its modal frequencies. A feedforward backpropagation neural network was designed, trained, and used to predict the delamination location using the experimental modal values as inputs. The experimental results demonstrate that the predicted delamination location and size error is small.