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The aim of this work was to use artificial neural networks (ANNs) to model the effect of mean tensile stresses on the fatigue resistance of an aluminum conductor steel reinforced. To train the ANN, fatigue data available for this type of conductor subjected to 2 different levels of mean stresses in the aluminium wires (49 and 74 MPa) were used. It is shown that the use of ANN enabled the construction of constant life diagrams (105, 106, 107, and 108 fatigue loading cycles) for the conductor. These results confirmed that the ANN is able to accurately estimate the effect of mean tensile stresses on conductor durability even considering just a limited number of data for its training.