Through batch and fixed-bed column operations, nickel ions were extracted from a contaminated aqueous media by adsorption onto silica gel-immobilized alunite (Sg@Aln). A three-layer backward-propagating network with an ideal pattern of 5-10-1 and 4-10-1 was used to train and validate an artificial neural network (ANN) model for process modeling and optimization in batch and continuous systems, respectively. For the test dataset, the model outputs of the model pointed out a satisfactory alignment between the anticipated and experimental response. The Sg@Aln dosage and contact time were recorded as the most relevant parameters in Ni