Many network resource management solutions typically employ traffic prediction algorithms to improve the performance of a network. In this paper we extend a newly developed method for prediction with confidence to time series data and apply it to the network traffic demand prediction problem. We investigate the performance of the proposed algorithm on a number of publicly available network traffic demand datasets. The experimental results are very promising.