Dependent data are popular in applications. The dependence described by strong mixing  is the weakest among well-known mixing structures, which appears in many application fields such as the pricing theories of financial assets. In this paper, by applying the blockwise empirical likelihood (EL) approach, the EL-based confidence regions for the regression vector in a linear model under strongly mixing errors are established, which can be used for the interval estimation and hypothesis testing of the regression vector. Results of a small simulation study on the finite sample performance of the confidence regions are provided.