In this research, the estimation of adult and nymph stages and adult of Aphis fabae was investigated using artificial neural network. Determining A. fabae nymph stages is difficult. Morphometric study of different parts of an insect's body is needed to obtain an index to distinguish between different immature stages. The study was aimed to develop a model of A. fabae nymph stages and adult using length of hind tibia, antenna and body length. It was found that the constructed artificial neural network (ANN) exhibited high performance for predicting A. fabae nymph stages. Correlation was 99% and the estimation of the best ANN model was determined to be 0.016289 at epoch 18. Soft ware computing techniques are very useful tools for precision agriculture and also determining which method gives the most accurate result.