Expert systems are one of the widely used artificial intelligence techniques and their use is increasing day by day. Expert systems are a technique that can use the knowledge and experience of experts, evaluate them at the decision-making stage and make inferences. Bolts are fasteners used to connect various parts and are within the scope of standard machine elements. There are different types of bolts in the industry and choosing the right bolt requires expertise. In this study, an expert system called Exbolt System, which selects bolts according to head types, was developed. Commonly used standard bolt types were based on bolt head types. Relevant rules for bolt types were established by collecting and analysing information about each bolt. While the rules were written, it was aimed to choose the truest bolt type. Criteria such as the need for fine-tuning, use in rotating parts, centring in the hole, flat surface requirement, mounting accuracy, system weight status, high force-holding and use in dirty environments were considered in the creation of the rules. The programme makes the best choice and recommends the bolt that can be used according to the head type to the user. CLIPS expert system programming language was used in the development of the Exbolt System. With the answers to the questions asked to the user by the programme, it was ensured that the truest bolt selection was made. The most accurate result was achieved by making faster, easier and more comprehensive decisions in the bolt selection, which requires expertise, and a more effective and efficient selection process was realised by saving time and labour.