A new Quantitative Structure-Activity Relationship model is introduced for reliable prediction of the toxicity of organic aromatic compounds based on the logarithm of 50 % growth inhibitory concentration of Tetrahymena pyriformis (log(IGC50−1)), which have extensive use in ecotoxicology and environmental safety applications. The largest experimental data set of log(IGC50−1) for 892 organic aromatic compounds is used to derive and test the new model. A core correlation based on additive variables is introduced by the number of nitro groups, carbon and halogen atoms as well as some specific polar groups and molecular weight. An improved correlation based on two non-additive correcting functions is developed for the increment of the reliability of the core correlation. The reliability of the improved correlation is tested and compared with two of the best available methods, which require complex descriptors. The predicted results for 661 and 231 of training and test sets have been confirmed by internal and external validations. The values of correlation coefficient (R2), mean error (ME), root mean squared error (RMSE), and maximum of errors (Max Error) for 661/231 of training/test aromatic compounds are 0.8442/0.7771, 0.0000/0.0149, 0.3166/0.3603, and 0.9732/0.9825, respectively, which are good results as compared to extra complex models with lower reported data. Various statistical parameters confirm the goodness-of-fit, high reliability, precision, and accuracy of the novel model.