The invention discloses a construction method of a neural network model for realizing image classification. The construction method comprises the following steps: S1, constructing a unit structure search network, a system structure search network, an image training set and a random coding array; s2, generating a neural network model by using the unit structure search network, the system structuresearch network and the random coding array; s3, inputting the image training set into a neural network model to obtain an actual classification result; s4, judging whether an actual classification result meets a preset condition or not, and if not, performing a step S5; s5, updating the unit structure search network and the system structure search network according to the actual classification result and the theoretical classification of the image training set; s6, repeating S2; And S5, until the actual classification result obtained in the step S4 meets the preset condition. According to themethod disclosed by the invention, an original search space is converted into two spaces, namely a unit structure search space and an architecture search space, the optimal architecture of the architecture is searched in an automatic learning manner, and the flexibility of the generated model architecture is enhanced.