The measurement and assembly of aeroengine rotor are separated from each other, the uncertainty of the test position leads to the test data cannot reflect the geometric characteristics of the rotor itself, which makes it difficult to accurately measure and predict the assembly accuracy. Combined with the fact that the geometric characteristics of parts / components are not related to the measurement datum, an assembly accuracy test and prediction method is proposed to reduce the datum deviation and ensure the consistency of test data. Firstly, the small displacement torsor is used to describe the datum deviation, the inverse matrix transformation is applied to reduce the datum deviation, and the datum independent matrix is utilized to express the pose characteristics of the parts / components, which provides the data basis for the accurate prediction of assembly accuracy. Then, the pose transfer model based on the datum independent matrix is established, which is more comprehensive and clearer than the traditional accuracy prediction model. Furthermore, a direct optimization method is also established, which is more efficient than the traditional genetic algorithm. The assembly experiment of aeroengine rotor shows that the model and method proposed in this paper are beneficial to reduce the coaxiality of the front and rear fulcrum and they can better reflect the geometric characteristics of the rotor itself. The related research also has reference significance for other large-scale and high-precision mechanical product assembly.