In the paper, a novel practical approach to construct a composite indicator (CI) is proposed. The key idea is to decide the weights of sub-indicators in constructing a composite indicator by maximizing the sum of squared correlations between the CI and sub-indicators. The CI obtained in this fashion has the maximum sum of squared correlations among all linear estimators. In addition, the simple, exact and explicit solutions of weights are proposed under the condition of non-negative irreducible matrix. Moreover, under this particular condition, the proposed method will become the principal component analysis. For illustration purpose, the proposed novel approach is utilized to calculate Sustainable Energy Index and Human Development Index which are two often-used cases to compare models in the literatures. The results show that the power of the proposed method outweigh the methods of Hatefi, et al. (2010) and Zhou, et al. (2007) in terms of the sum of absolute values of all sub-indicators’ correlations.