Optimal descriptors based on the simplified molecular input line entry system (SMILES) have been utilized in modeling of carcinogenicity. Carcinogenicity of 401 compounds has been modeled by means of balance of correlations for the training (n = 170) and calibration (n = 170) sets. The obtained models were evaluated with an external test set (n = 61). Comparison of models based on the balance of correlations and models which were obtained on the basis of the total training set (i.e., both training and calibration sets as the united training set) has shown that the balance of correlations improves the statistical quality for the external test set.