Artificial neural network is a class of machine learning models that can be used for various applications, such as image recognition, natural language processing, stock market prediction, target marketing, credit rating, medical diagnosis, and speech recognition. This study examined the performance of various artificial neural network’s algorithms on a classification problem. The results of this study showed that resilient back propagation algorithm performed better in comparison to others artificial neural network algorithms in term of misclassification error. The outcomes of this study are helpful for researchers as well as practitioners in the field of machine learning modeling.