<![CDATA[Expert systems are a branch of artificial intelligence designed to replicate the reasoning ability of specialists. This study applies the forward chaining method to build a web-based expert system for diagnosing laptop malfunctions. The system’s knowledge base was constructed from 20 common laptop malfunction symptoms, identified through literature review, user questionnaires, and interviews with repair technicians, and translated into inference rules. To evaluate performance, the system was tested on 50 malfunctioning laptops. Results show that the expert system achieved an accuracy rate of 85%, indicating its effectiveness in detecting various hardware and software problems. This research demonstrates that forward chaining can support non-expert users in performing early fault detection, thereby reducing repair costs and dependence on professional technicians]]>
