The existing results about the analysis and control of logical networks are theoretically perfect, but can hardly be applied to large-scale logical networks because of high computational complexity. Recently, several efficient methods have been developed to study large-scale logical networks, including network aggregation [1], logical matrix factorization [2], node removal [3] and compositional framework [4]. This chapter introduces these four methods, and presents the corresponding applications in large-scale logical networks.