Abstarct: In this work, the carbon dioxide uptake by amine-functionalized porous polymers has been predicted using the group method of data handing (GMDH) approach. 5 descxriptors including temperature, pressure, molecular weight of monomer that forms the baxse polymer, inverse of pore volume and molecular weight of amine lixnker were selected for modeling. 946 CO2 uptake experimental data points with 53 different amine-functionalized porous polymers over a wide range of temperatures and pressures were gathered. 662data points were divided as train and internal test sets in the ratio of 70:30 and 284 data point were considered as external set for model evaluation. After training and optimization of the model parameters and architecture, the performance of the optimized model were evaluated by the test sets (internal and external). The root mean square error (RMSE) and standard error (SE) were obtained for the internal test set 0.219 and 0.229 and those for external test set 0.147 and 0.141, respectively. The results showed that the optimized GMDH model can predict the carbon dioxide uptake with amine-functionalized porous polymers accurately in a wide range of temperatures and pressures.