The invention provides a micro-droplet data classification method. The method comprises the following steps: inputting micro-droplet data and classification form parameters of micro-droplets; dividingthe micro-droplet data into grids, wherein all the grids form a grid atlas; dividing the grid atlas into at least one area according to the density difference of the micro-droplet data in each grid;setting a reference point combination according to the classification morphological parameters, comparing the reference point combination with the center of each region, and determining optimal classification morphological parameters; and classifying the micro-droplet data according to the number of the regions. The classification method can be used for automatically, objectively and accurately carrying out unsupervised and self-adaptive classification on various common micro-droplet data.