To identify a Saccharomyces cerevisiae fed-batch fermentation process, it is suggested that a differential (dynamic in continuous time) neural network (DNN) be implemented. A priori information on the dynamic equations and their parameters is not required to realize this approach. Based on real data, obtained from laboratory experiments, this DNN of a simple structure (six neurons) is shown to have a high capability of identifying this process (to reproduce the input±output relation) after several working hours of learning.