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Azo dyes are broadly used in different industries through their chemical stability and ease of synthesis. However, these dyes are usually identified as critical environmental pollutants. Hence, a mathematical model for the adsorption affinity of azo dyes can be applied for solving tasks of medicine and ecology. Quantitative structure-property relationships for the adsorption affinity of azo dyes to a substrate (DAF, kJ/mol) were established using the Monte Carlo method by generating optimal SMILES-based descriptors. The index of ideality of correlation ( IIC ) and the correlation intensity index ( CII ) improved the model’s predictive potential, especially when they were used simultaneously. The statistical quality of the best model on the validation set was characterized by  n  = 18,  r2  = 0.9468, and RMSE = 1.26 kJ/mol.

Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential