The classification of drugs was done according to their milk/plasma concentration ratio (M/P) by using counter propagation artificial neural network (CP-ANN). The features of each drug were encoded by linear free energy relationship (LFER) parameters. These descriptors were used as inputs for developing linear discriminant analysis, quadratic discriminant analysis, least square support vector machine and CP-ANN models to distinguish the potential risk of 154 drugs as high risk (with M/P > 1) and low risk (with M/P < 1) for lactating women. The accuracy of classification for training, internal and external test sets was 100.00%, 100.00% and 90.00%, respectively for CP-ANN model, as the best model. The obtained results revealed the applicability of CP-ANN in classification of drugs based on their M/P values, using LFER parameter
