The combine harvester knowledge base system uses the SQL server database, numerous data tables in the database are independent and easy to build and manage. But when the amount of knowledge base data reaches a certain size, querying data tables one by one is not actionable and merging all the data tables will lead to confusion in the data structure, unclear content expression, and technical inability to achieve. In response to this problem, a multi-table joint query method of combine harvester knowledge base data was proposed. The data table types was divided from multiple perspectives, the data storage structure of the combine harvester knowledge base was analyzed and the management scope for multi-table joint data was set. The application structured query language (SQL) fused multi-table information into a dataset and stored it into a temporary table to achieve multi-table joint operation. The human-computer interactive interface was used to convert the user query requirements into multi-table joint query statements to generate query results, and multi-table approximate range query and multi-table precise positioning query were realized. The test results between multi-table joint query and traditional single-table knowledge query showed that on the one hand, multi-table approximate range query saved user operation time by 50% or more than the original single-table approximate range query of the system, and the highest reached 90.4%;on the other hand, the multi-table precise positioning query saved 48.1% or more user operation time compared with the original single-table precise positioning query of the system, and the highest reached 89.6%. The implementation of multi-table joint query made the combine harvester knowledge base system practical and feasible and provided a reference idea and method for data management of similar knowledge base system.