The residuals of the final and optimized QSAR regression model were between -1 and 1 in LC50 units for ≈ 95% of the data (Figure ). This model consisted of 600 trees and 8 variables, resulting in an R 2 of 0.86 for the training set and ≈ 0.7 for both median cross-validation and test set. The observed levels of accuracy was comparable to previously reported linear and non-linear QSAR models (Figure ). We observed up to 2.1 log(mg/L) overestimation of the LC50 for values ≤ -1 while our model resulted in a slight underestimation of toxicity for LC50 values ≥ 5 (Figures and). Finally, we used the optimized model to predict the 96h acute fish toxicity LC50 values for the Norman dataset. When comparing the results of our predictions to the predictions by Aalizadeh et al, 34 a clear linear trend (i.e.