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The most influential parameters on polymerization of ethene + oct-1-ene using a metallocene catalyst system are temperature, ethene pressure, and the amount of hydrogen used for polymerization. An implemented artificial neural network (ANN) is a supervised back-propagation model with different architectures. An ANN for determining the conditions in the copolymerization of ethene + oct-1-ene using a metallocene catalyst system to produce a copolymer with specific chains has been implemented. It has been shown that the proper functioning of the ANN is implemented with satisfactory R values. Therefore, it is concluded that the ANN developed is an effective tool to determine the conditions of copolymerization of ethene and oct-1-ene.