To satisfy the requirements for secondary equipment condition-based maintenance from distribution network lean operation, this paper proposes a condition diagnosis method for Distribution Terminal Units (DTU) on the basis of multi-source information fusion concept. Three kinds of easily collected condition features are put forward by analyzing DTU monitoring information, thus the corresponding evidence framework is built. The Basic Probability Assignment (BPA) function constructor is presented, where the expertise-based weighted average fuzzy membership instead of correlation coefficients is utilized for calculation in order to avoid the training biases derived from the lower quantity of faulty DTUs. Multi-source information fusion is achieved by D-S evidence combining theory, and DTU condition is diagnosed according to the BPA decision rules. Finally, a case study of DTU condition diagnosis is carried out, where the results validate the effectiveness of this proposed method. This work is supported by National Natural Science Foundation of China (No. 51407128), Science and Technology Project of State Grid Corporation of China (No. 5216A016000T), and Science and Technology Project of State Grid Hunan Electric Power Company (No. 5216A515008).