This research addressed the issue of the forecast of the volume of fresh avocado sales of the company Avocado Packing Company S.A.C. by means of artificial neural networks (RNA). The objective was to determine the level of precision of the artificial neural networks used in a forecasting model for fresh avocado exports. The methodology consisted of defining the input and output variables, such as dispatch weeks, price, per capita consumption and sales volume; which were used to establish the number of input and output neurons. Subsequently, the design of the network was carried out with the Backpropagation training algorithm and the purelin function to obtain output data. The values of hidden layer neurons and learning rate were obtained according to the lowest mean square error (MSE) value and the highest value of the correlation coefficient (R) in the training stage. In this stage, the...