Ojo, A. K.Adeyemo, A. B.2025-10-1320132167-1710ui_art_ojo_comparison_2013Computing, Information Systems, Development Informatics and Allied Research Journal 4(2), pp. 15-22https://repository.ui.edu.ng/handle/123456789/11356In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to determine which of them performs better. Prediction was done using one hidden layer and three processing elements in the ANN model. Furthermore, prediction was done using regression analysis. The parameters of regression model were estimated using Least Square method. To determine the better prediction, mean square errors (MSE) attached to ANN and regression models were used. Seven real series were fitted and predicted with in both models. It was found out that the mean square error attached to ANN model was smaller than regression model which made ANN a better model in prediction.enArtificial Neural NetworksRegressionLeast SquareProcessing ElementHidden LayerMean Square ErrorArticle