This paper aims to study the effect of extra water, magnetized water, and fly ash/GGBFS ratio on the mechanical behavior of fly ash-based geopolymer concrete blended with various GGBFS contents (5, 10, 15, and 20, 25%, by mass of fly ash) using the artificial neural network (ANN). Tap water and Magnetized water were used in this study. Different amounts of extra water (10, 15, 20, 25, and 30%, by mass of binder) were considered. The ANN model adopted in this research consists of three neurons in the input layer representing extra water, magnetized water, and fly ash/slag ratio and one neuron in the output layer which represent the compressive strength. The results obtained in good correlation with the ANN results, where, ANN-based model gives very close estimates of the 28 days compressive strength.