The process of plasma enhanced chemical vapor deposition silicon nitride films coated on silicon solar cells as antirefltion layers is modeled and optimized using neural networks. This neural network model is built based on the robust design technique with process input-output experimental data. The input parameters selected are as substrate temperature, SiH4 and NH3 flow rates, and RF power; while the output parameters are deposition rate, refractive index, and short circuit current. This model can then be applied to predict the input-output relationships, of the process, Optimal operating conditions of this process can be determined using this model, (C) 2002 Elsevier Science B.V. All rights reserved.