Vulvodynia is a chronic pain condition affecting the vulva that significantly impacts women’s quality of life. Accurate and early diagnosis poses a challenge due to the often-overlapping symptoms with other conditions and the lack of definitive diagnostic tests. This paper proposes the use of expert system methods as a diagnostic tool for vulvodynia in women. The expert system, integrating medical knowledge with inference algorithms, is designed to analyze symptoms, medical history, and test results to provide accurate diagnoses and treatment recommendations. The study involves the development and evaluation of a computer-based expert system prototype that uses clinical data and medical decision-making to enhance the accuracy of vulvodynia diagnosis. Preliminary results indicate that the expert system can improve diagnostic rates and reduce the time required for identifying this condition, offering a potentially valuable tool for medical professionals in clinical practice.