Ultrasonic identification has an important application value for national defense, military affairs, aerospace, nuclear facilities and other high-tech fields. Ultrasonic waves can be used to identify any metal material. At present, the researches focus on algorithms for identifying the difference in ultrasonic signal among materials, but the study on the corresponding identification theory is lacking. In this work, 10 primary models of the microstructure of 2A12 aluminum alloy are established as analogies to the complex microstructures of polycrystalline metallic materials. The grains of these models are different from each other in size, separation distance, shape, arrangement directions and orders. The time-domain ultrasonic echo signals of different microstructures are calculated by making use of the finite element method. The grass-like signals between two echoes are ultrasonic backscattering signals, which are sensitive to any change of microstructure. The backscattering signals between the primary echo and the secondary echo in the ultrasonic echo time domain signals are extracted as ultrasonic fingerprints. The feature difference Qis defined to quantify the difference in ultrasonic fingerprint of each sample. The results show that the slight variation in microstructure will lead to difference in ultrasonic signal, and the difference caused by the variation in grain size is more distinct. And then, an ultrasonic identification algorithm is proposed, and the identification experiments are conducted on four 2A12 aluminum alloy samples with the same shape. The identification results show that the target sample can be accurately identified by using ultrasonic fingerprints and the ultrasonic fingerprints of the target sample are distinctly different from those of the other samples. The microstructure morphologies of the samples are examined by using scanning electron microscopy (SEM). The SEM results show that there are significant differences in grain size, separation distance and densification between samples although they are the same material. The features of the microstructure in the proposed ultrasonic scattering model in this work are confirmed by the actual y micromorphologies observed in the SEM images. The identification experiments and SEM results demonstrate that the established ultrasonic scattering model is effective. This work can provide a reference for theoretically studying ultrasonic identification and present an idea for developing some new identification algorithms in future.