In this talk, we will discuss a novel eigenvalue-based approach to solving the unbalanced orthogonal Procrustes problem. By making effective use of the necessary condition for the global minimizer and the orthogonal constraint, we shall first show that the unbalanced Procrustes problem can be equivalently transformed into an eigenvalue minimization whose solution can be computed by solving a related eigenvector-dependent nonlinear eigenvalue problem. Through the exploitation of certain techniques in the nonlinear eigenvalue computations, we adapt the standard self-consistent field (SCF) iteration to solve the resulting nonlinear eigenvalue problem. Theoretical convergence analysis of this customized SCF iteration is performed, and practical strategies for a more efficient numerical implementation are discussed. Our numerical experience on preliminary tests indicates that the proposed eigenvalue-based SCF iteration is a promising method for the unbalanced orthogonal Procrustes problem.