A general Quantitative Structure-Activity Relationship (QSAR) model onVibrio fischeri(Microtox™test) was derived using the autocorrelation method for describing the molecules and a neural network as statistical tool. From a training set of 1068 organic chemicals described by means of four different autocorrelation vectors, it was possible to obtain valuable models but presenting some large outliers. Addition of the time of exposure as variable allowed us to derive a more powerful model from 2795 toxicity results. The predictive power of this 36/26/1 neural network model was tested on an external testing set of 385 toxicity data and compared with the performances of linear models designed for polar narcotic amines and for weak acid respiratory uncouplers.