The purpose of this chapter is to model a petrochemical unit by neural networks to estimate the product flow rate of the plant by it. Multilayer perceptron and RBF neural networks have been used in this work, and finally, the outputs of both types of networks have been compared to choose the more accurate network. The same data have been used for training and modeling both networks. The data used for this modeling have been collected by measuring the flow rate of input materials and output products from the plant in ton per day. Table 1 shows the input materials and products.