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The physical properties, like density and viscosity, of alkanolamine + H₂O (water) + CO₂ (carbon dioxide) mixtures receive a significant amount of attention as they are essential in equipment sizing, mathematical modelling and simulations of amine-based post-combustion CO₂ capture processes. Non-linear models based on artificial neural networks (ANNs) were trained to correlate measured densities and viscosities of monoethanol amine (MEA) + H₂O, MEA + H₂O + CO₂, and 2-amino-2-methyl-1-propanol (AMP) + MEA + H₂O + CO₂ mixtures and results were compared with conventional correlations found in literature. For CO₂-loaded aqueous amine mixtures, results from the ANN models are in good agreement with measured properties with less than 1% average absolute relative deviation (AARD). The ANN-based methodology shows much better agreement (R² > 0.99) between calculated and measured values than conventional correlations.