In recent years, there was great interest and demand for the production and investigation of low cost and novel transparent conducting oxide films. CdO is a promising material among these films for future applications with its unique properties. A learning and generalization ability, real-time operation, and ease of implementation have made an artificial neural network popular in recent years. In this work we have produced CdO:Sn films by the ulrasonic spray pyrolysis technique which is economical and simple to process. Optical parameters of Sn doped CdO films with developed, have been estimated by the artificial neural network using experimental results as a training data. The correlation obtain from the artificial neural network was found to be 99% with the experimental results.