This paper introduces a new temporal neural networks model which can be used in connectionist expert systems. Also, a Variation of backpropagation algorithm, called the temporal feedforward backpropagation algorithm is introduced as a method for training the neural network. The algorithm was tested using training examples extracted from a medical expert system. A series of experiments were carried out using the temporal model and the temporal backpropagation algorithm. The experiments indicated that the algorithm produces correct results and the model correctly represents explicit sequences of time. Another advantage of the algorithm is possibility of implementing it on general purpose parallel machines. The paper briefly discusses the parallelism issues of this algorithm.