The application of information systems is handy for business needs as well as the needs of human activity. One form of an information system is an expert system, which is used to transfer human thinking abilities to computers, capable of solving problems like how experts think. The problem that often occurs with mechanics or excavator operators is the limited number of experts to provide consultations to mechanics who need solutions to damage that occurs to machine parts. This study uses the forward chaining method to describe the identification, diagnosis, and explanations of excavator engine damage. The knowledge representation used is IF-THEN rules and combining rules that can produce a conclusion. Forward Chaining has a fact-based search technique which is then matched to find directions. The forward chaining method in several studies is able to produce good accuracy values. In making this system, it is hoped that experts in the field of heavy equipment engines and several manuals about excavator machines will get accurate data about machine damage information. Applying the forward chaining method to this expert system can produce an accuracy rate of 90% through 10 tests