In this research, PSA process was studied to purify hydrogen from methane using activated carbon as adsorbent. This process is extensively used for purification of hydrogen in the hydrogen production units. The purge-to-feed (P/F) ratio and adsorption time were considered as variables. Moreover, the PSA process was modeled by considering all the important parameters such as hydrogen purity percent, recovery, and productivity. The central composite design (CCD) was used for experimental design, modeling, and optimization of the process. With this method, a model was applied for each parameter regardless of complex and time-consuming equations which generally were employed in the literature. The statistical analysis reveals that for each response, a distinct second order polynomial equation with F-value more than 300, p-value less than 0.0001, and R-squared more than 0.993 is able to predict the response. Furthermore, the predicted value from models had no significant difference with experimental values. Based on established models, as the purge-to-feed (P/F) ratio increased, the hydrogen purity increased, while the recovery and productivity decreased. The recovery and productivity first increased and then decreased as adsorption time increased. As adsorption time increases, purity has approximately constant value up to 10 min and then declines that can be attributed to less amount of available fresh adsorbent at a higher adsorption time. Moreover, with respect to models, the parameters were maximized.