In this paper, we present the design and implementation of an image analysis system for the automatic analysis of Heliothis zea insect images. The Heliothis zea is a corn earworm eating corn crops. Biotech researchers are interested in developing insecticidal bio-toxins with the best performance to kill or stunt the growth of this insects. The automated analysis of Heliothis zea images is imperative for fast and efficient biotech experiments. The proposed system consists of three stages: (i) insect segmentation, (ii) region processing, and (iii) instar and life classification. A probabilistic model (PM) based on mixtures of Gaussians has shown better performance for segmenting the insect images. And a back-propagation neural network (NN) has shown better performance for classifying the insect instar stage. The proposed system has been evaluated on real data using a five-fold cross validation procedure.