The invention discloses an age estimation method based on a multi-output convolution neural network and ordered regression. The method comprises the following steps of 1, establishing an Asian face age data set (AFAD); 2, establishing training data used for a dichotomy; 3, training a depth convolution neural network; 4, inputting a test sample into a trained convolution neural network; and 5, acquiring age estimation of the test sample. The invention provides a method of sorting the ages. The ordered regression and a deep learning method are combined so that accuracy of age prediction performance is greatly increased. In an existing age estimation method, characteristic extraction and regression modeling are performed independently and optimization is insufficient. By using the method of the invention, the above problems are solved; a sequence relation of age labels can be fully used to carry out ordered regression of age estimation; age estimation accuracy is increased; a large scale database is established for the age estimation of the Asian faces and a database basis is provided for face age estimation research. The method can be widely used for age estimation of face images.