Pharmaceuticals pose a risk to human health and the environment, even at trace levels. They constitute a significant class of potential endocrine disruptors, so they have drawn special attention from the international scientific community. Sulfamethoxazole is an antibiotic compound that eliminates the bacteria that cause many infections but not for colds, flu, or other virus infections. It belongs to the sulfanilamide medication class, with the basic molecular arrangement of SMX (C10H11N3O3S). Among a large number of advanced oxidation processes, UV/chlorine is one of the few AOPs that have been developed and implemented because of its benefits. In this research, the removal of sulfamethoxazole onto activated carbon from aqueous solutions was studied at varying pH levels under constant process parameters. Also evaluated different variables affecting the process like pH in the range of (3-9) at which the higher degradation was observed at normal (pH = 7) at the shortest retention time (RT = 5 mins), and varying SMX concentrations. It was noticed that the linear correlation of the batch process fits the Pseudo-Second Order (R²≥ 0. 0.9418) in the GAC adsorption of the optimal retention time experiment. The Freundlich and Langmuir equations have been used to represent adsorption isotherms for the reactions. Freundlich model performed best fit the equilibrium with heterogeneous activated carbon process adsorption. The pseudo-first order and pseudo-second order models were discussed considering kinetic models. With the use of the MATLAB® package program, non-linear regression was used to get the parameter values for the selected adsorption isotherm models. A multilayer perceptron artificial neural network (MLPANN) was generated as a model for SMX removal prediction. The multilayer perceptron (MLP-ANN) has been found to perform well in predicting response values.