Control chart is the main and powerful tool in statistical process control in order to detect and classify data, either in control or out of control. Its concept, basically, refers to the theory of prediction interval. Accordingly, in this paper, we aim at constructing of what so called predictive bivariate control charts, both classical and Copula-based ones. We argue that appropriate joint distribution function may be well estimated by employing Copula. A numerical analysis is carried out to illustrate that a Copula-based control chart outperforms than other.