The classification of stellar spectra is an important job in data processing of astronomy, which is mainly used for searching celestial spectra with known types in massive data survey. This paper focuses on LAMOST M dwarfs fine classification based on measurement of residual distribution. Residual distribution measurement is a measurement method used to measure the distance between two spectra. In the process of calculating the distance between two spectra, normalized processing should come first. Then the residuals of the sampling points of corresponding wavelength are calculated. Eventually the standard deviation of the residual distribution as the distance between the spectra is calculated. In this paper, the M star of LAMOST DR2 is used as the experimental data of classification. The experimental results show that the spectra data can be classified more accurately with the measurement method of residual distribution than the use of other traditional classification methods. The effect of spectral classification is affected by signal to noise ratio, outliers, residual standardized coefficient and other factors.