In recent years, industrialization causes excess carbon dioxide emissions. Carbon dioxide (CO2) is one of the main greenhouse gases due to human activities. However, high costs remain the main challenge to control the carbon dioxide from industry. Due to this issue, the carbon capture technique is developing slowly in most developing countries. This work is going to compare and explore a more effective blended amine solvent comparing with current common single amine solvents for the CO2 chemical absorption process for improving absorption performance and reducing the investment and operating costs. In this research, the CO2 absorption performance of aqueous MDEA/PZ blends and aqueous MEA/MDEA/PZ blends were comprehensively investigated experimentally and compared with the benchmark aqueous solution 5M MEA in terms of CO2 absorption rate, CO2 absorption efficiency, mass transfer efficiency and CO2 equilibrium solubility using a bench-scale packed column and a CO2 solubility apparatus. The simulation results have been validated with the experimental date from this research work other published experimental data. Different scenarios were assessed to evaluate the absorption performance using experiment method and simulation method. The overall mass transfer coefficient of the aqueous solvents and the CO2 absorption rate under ambient pressure is ranked as 2M MDEA+3M PZ>1M MEA+2M MDEA+2M PZ > 3M MDEA+2M PZ > 5M MEA. The measurements of the CO2 solubility experiments were performed over the CO2 partial pressure range of 8-51 kPa at 40oC. A new set of experimental data for the CO2 solubility in an aqueous solution of 1M MEA+2M MDEA+2M PZ blended solvent and aqueous MDEA/PZ blends were investigated and compared with the prediction results from the Artificial Neural Network model and the simulation results using MATLAB and ProMax, respectively. The prediction results from ANN model confirmed that the CO2 equilibrium solubility of 2M MDEA+3M PZ was higher than other blend amine solvents and the conventional amine (5M MEA). Also, the comparison results indicate that the neural network modeling provides more accurate prediction results of CO2 solubility test than the simulation results when compared with new experimental results in this research.