The accurate phase and meter box information of single-phase users in low-voltage courts have great impacts on the checking of user-transformer relationships and the treatment and analysis of line losses. At present, the correction of topological documents mainly relies on the on-site checking by electrical engineers, which spends a lot of manpower and material resources with low efficiency. Therefore, it is necessary to study a more efficient method of checking the topological documents of the low-voltage courts. In this background, a phase and meter box identification method based on voltage measurement data of smart meters is proposed, which provides reference for topology identification and correction of low-voltage courts. Firstly, the t-distributed stochastic neighbor embedding (t-SNE) technology is adopted to reduce the dimension of original load data, so as to solve the redundancy problems caused by excessively high dimension of original load characteristics of users. Then, the balanced iterative reducing and clustering using hierarchies (BIRCH) method is used to cluster the dimension-reduced load data, so as to identify the phase and meter box information of single-phase users. Finally, case studies for an actual low-voltage court in Haining of Zhejiang Province, China, are performed to verify the correctness of the proposed method, and the results show that the proposed model is feasible and effective.