This paper is focused on pattern recognition for Heterocyclic chemical handwritten recognition using Neural Networks. The idea is to develop a software to make the recognition simple with a very high accuracy. The development stage is based on two phases. In the first phase, a neural network is used as a classifier to classify to which class the chemical rings can be classified, where four classes are defined (S, N, O and others). In the second phase, a neural network to recognize the type and name of the chemical rings within the classified class in the first phase is performed. A comparative study has been done to distinguish the results of various used approaches.