Objective: This paper presents a summary of web-based data collection, impact evaluation, and user evaluations of an Internet-based peer support program for Ménière’s disease (MD). Design: The program is written in html-form. The data are stored in a MySQL database and uses machine learning in the diagnosis of MD. The program works interactively with the user and assesses the participant’s disorder profile in various dimensions (i.e., symptoms, impact, personal traits, and positive attitude). The inference engine uses a database to compare the impact with 50 referents, and provides regular feedback to the user. Data were analysed using descriptive statistics and regression analysis. Study sample: The impact evaluation was based on 740 cases and the user evaluation on a sample of 75 cases of MD respectively. Results: The web-based system was useful in data collection and impact evaluation of people with MD. Among those with a recent onset of MD, 78% rated the program as useful or very useful, whereas those with chronic MD rated the program 55%. Conclusions: We suggest that a web-based data collection and impact evaluation for peer support can be helpful while formulating the rehabilitation goals of building the self-confidence needed for coping and increasing social participation.