Analogical reasoning is one of the most common forms of thinking that people use existing knowledge to reason, and it is a key phenomenon of human intelligence. However, when analogical reasoning is faced with simple reasoning tasks, the result is not accurate. Computationally complex problems arise when faced with complex inference tasks in big data. In order to solve the problem of analogical reasoning, based on the [U, I] image matching principle in factor space theory, this paper proposes a factor analogical reasoning model, gives the steps of factor analogical reasoning algorithm, analyzes an example in UCI data set, and compares and analyzes the factor analogical reasoning algorithm proposed in this paper with the factor analysis algorithm. The results show that the factor analogy reasoning algorithm proposed in this paper can realize the effective reasoning of the analogy reasoning problem, and the algorithm has the advantages of accurate calculation results and short calculation time. The conclusion of analogical reasoning based on factor space expands the theory and application of factor space.