This article presents a methodology for computational prediction of LOER on well-ordered oxide structures, exemplified by a case study of the rutile Ru 1-x Ni x O 2 (110) and Ru 1-x Ti x O 2 (110) surfaces. This is done by calculating the binding energies of the oxygen atoms in the surface for all different local configurations including one to three metal atom substitutions in the surface layer. This allows for identification of weakly bound oxygen atoms that could potentially be evolvable. A volcano plot for such active sites is then established, and allows for prediction of LOER activity and active sites. For the case of Ru 1-x Ni x O 2 it is found that LOER should be active at elevated electrode potentials, matching experimental findings in the literature. The LOER active sites are found to be mainly Ru-Ni bridge sites. This result forms a direct link between surface structure and LOER activity, assuming that more LOER active sites result in higher LOER activity. By applying experimental knowledge of the clustering mechanisms of nickel in this system it is possible to construct a model of LOER activity as a function of nickel content in the catalyst. The resulting model predicts that the maximum LOER activity should be found between x = 12.5% and x = 20%.