Artificial intelligence based techniques capitulate better performance in identifying the intrusions than other conventional approaches used in this field, but no single classifier is capable of identifying intrusions with acceptable accuracy. So, there is a necessity of integrating more than one classifier. This paper mainly focuses on constructing an ensemble of classifiers for classification of network traffic. In ensemble approach numerous machine learning algorithms are pooled. The main inspiration behind combining these classifiers is to take advantage of the powers of each classifier of the ensemble to get an overall more accurate classification.