Acne vulgaris is a polymorphic skin disease with various clinical manifestations that can affect both the physical and psychological conditions of sufferers. Limited public knowledge and access to dermatological healthcare services have increased the need for an easily accessible early diagnostic support system. Previous studies have generally focused on identifying types of acne without integrating severity classification as part of the system output, resulting in limited information provided. This study aims to develop a web-based expert system using the Certainty Factor (CF) method that not only identifies types of acne vulgaris but also determines their severity levels. The system’s knowledge base consists of six types of acne, three levels of severity, and 24 symptoms obtained through literature review and expert consultation. The inference mechanism is carried out by calculating the CF value for each symptom based on the multiplication of expert confidence values (MB–MD) and user confidence levels, followed by combining multiple CF values using the CF Combine formula to obtain the final CF value for each type of acne. The diagnosis is determined based on the highest CF value obtained. The results of Black Box Testing indicate that all system functions operate as expected. Usability evaluation using the System Usability Scale (SUS) yielded an average score of 75.25, which falls into the acceptable category with a grade B (Good), indicating that the system is well accepted by users. This system is expected to serve as a supporting tool in obtaining preliminary information about acne conditions in a fast, accessible, and accurate manner.