This paper presents result of QSTR (quantitative structure–toxicity relationship) study obtained using the PRECLAV software. The dependent property is toxicity against rat (Rattus norvegicus), measured by TD50 values. The calibration/training/learning set includes 49 molecules having a very high chemical diversity. There are five outliers in calibration set. In the presence of outliers the predictive power of QSTR is very low (r2 = 0.5425, F = 10.4,
). After elimination of outliers the predictive power of QSTR is much higher (r2 = 0.9078, F = 44.3,
). All eight predictors are nonlinear functions (parabolic and products) of descriptors. The LogP is not predictor. Presence of C = CH2 and N–NO molecular fragments increases toxicity. Presence of C6H4 molecular fragment decreases toxicity.