The invention discloses a line loss rate prediction method based on non-isometric weighted grey model and fuzzy clustering sorting. The method is characterized in that grid electricity supply amount, grid investment, total electricity consumption, primary industry electricity consumption, secondary industry electricity consumption and tertiary industry electricity consumption are used as the feature data of each year, prediction samples are selected as comparison objects, and fuzzy clustering sorting is performed on historical data according to the similarity of features and the comparison object; fuzzy clustering sorting is performed on the historical data according to influence factors, and a weight matrix is introduced to give weight to the sorted historical data so as to allow the influence of data on grey modeling to be difference. The method has the advantages that the effect of prediction results is further optimized, and influence of economic factors on line loss rate prediction is minimized; the defect that the historical data is easily affected by economic factors to cause prediction result errors is overcome; information loss of a single mode can be avoided by combined prediction, randomness is reduced, and prediction precision is increased.