The study developed and evaluated a prediction model for drinking water consumption in the city of Iquitos, using a sample of size 288 obtained from historical data from SENAMHI, INEI, and SEDALORETO. A quantitative, applied, and non-experimental correlational approach was used to build and test an Artificial Neural Network (ANN) model, comparing model results with historical consumption data. The accuracy of the model was evaluated using algorithms and statistical models in MATLAB, using indicators such as Mean Squared Error (MSE), Correlation Coefficient (R), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R2). The results showed that the RNA model presented a high performance in terms of precision in the training, validation and test set, with MSEs of 99736607.27x10-8, 283364279.46x10-8 and 373108841.22x10-8, and correlation coefficients (R) of 0.996463, 0.986...