This paper presents experimental results related with the behavior of fiber optic microbend sensors based on different configurations. Different types of deformer sets having different mechanical periodicities, corrugation size and number of deformations cycles have been used to test the validity of the proposed technique. Normalized output intensity of the microbend sensor as a function of applied force is later used in the prediction of desired sensor response using Artificial Neural Networks (ANNs). It is shown that, ANNs can detect measurement errors and can be used in the development of intelligent and robust sensors that can monitor and detect the abnormalities in the sensors state. © 2010 IEEE.