This communication shows a novel strategy in the field of potentiometric sensors, applied to the determination of nitrate in the presence of chloride interferent. The determination is performed employing the flow-injection analysis technique with four potentiometric sensors featuring cross-term response. The signal processing with a multivariate data treatment, in this case an artificial neural network based on the Bayesian regularization, lets us quantify the concentration of nitrate ion between 0.1 and 100mgl−1NO3− without the need to eliminate chloride interferent. Results obtained with this approach are compared with the direct determination of nitrate using its ion-selective electrode, showing how the new strategy attains a better correlation of obtained versus expected values, especially at the lower concentration levels. The comparison line between these pairs yields an intercept of 0.0±0.3mgl−1NO3− and a slope of 1.01±0.02.