Water is a basic necessity in our daily activities. Therefore, there should be enough supply of water to meet with our demands. By average, in Cebu City, Philippines alone, 24 cubic meters per household per month is used [1]. To meet the demand, water has to be properly distributed considering several factors, which are: (1) temperature, (2) precipitation, (3) population, (4) water rates, (5) historical water use, (6) water supply, and ( 7) socioeconomic pro ile. This study developed an Arti icial Neural Network (ANN) water distribution decision support system that was able to predict water demand. The ANN was trained using historical records of the above-mentioned factors, and was able to provide municipal, and barangay water demand predictions with accuracy above 90%.