Agricultural machinery professional chassis has many types of parameters and their difference between each other is so large that they cannot be fully compensated without any price. For these characteristics, the classical nearest neighbor algorithm which relies on weight properties in case-based reasoning is unacceptable in practice. Aiming at the situation above, the sorted method ELECTRE, belonging to multiple attribute decision, which was characterized by outranking relationship, was applied to the similarity assessment. In this algorithm, the first step was data preprocessing; then AHP was adopted to determine attributes’ weights; after that harmony and disharmony thresholds were obtained by constantly experimenting adjustment; and then construction and mining of relationships were carried out; the ultimate goal was to accomplish similarity assessment between design case and database cases. After that, crawler of walking system and chassis prototype were used for verification of the algorithm. Compared with the nearest neighbor method, the algorithm not only returned the former models which had higher overall similarity, but also marked the key parameters that affected the order, allowing users to have more followup evaluation. To make the algorithm to be more practical, a prototype interface of CBR was developed and the input of critical parameters and output of results were demonstrated. The overall result was good.