To explain the behavior of a whole system, we may need more than one multiple regression with its own set of explanatory variables. Seemingly Unrelated Regressions (SUR) is a way to model these equations simultaneously. In this approach, the cross‐correlation between equations will be accounted in the estimation of regression coefficients. SUR has been used in many different areas such as econometrics, environmetrics, and social science. In this article, we discuss SUR model and some of its extensions, along with some of its applications.