In order to reasonably and scientifically select the smart meter with the smallest error to supply electricity to customers, a data mining and analysis method for smart meter error based on Gaussian mixture model is designed. First, the basic ideas of Gaussian mixture model and EM algorithm are analyzed. Secondly, the standard deviation of the smart meter error data is calculated as the modeling data, and the error data model of the smart meter based on the Gaussian mixture algorithm is established. Finally, it is combined with the traditional Kmeans. Class algorithm model for comparison test. The experimental results show that compared with other clustering algorithms, the designed method has a larger contour coefficient value and better performance. It can be used to find the smart meter with the smallest error in a large amount of data, and it can give feedback to the smart meter manufacturer on the product, and it also has functions such as product market division.