Worsening congestion conditions, high energy consumption, and environmental crises have paved the path for water transportation to re-emerge in the transportation industry after being neglected for many decades. Kochi, as one of the major port cities in India, which is enriched with navigable waterways has taken the initiative to launch the first water metro system of India, an integrated electric ferry transportation system, becoming the first of Asia in the same category. The newly emerged public transport facility is designed to cater both recreational riders and commuters. However, ridership data indicates that while recreational users have accepted the system, commuter riders remain hesitant. Therefore, this study will specifically focus on assessing the service quality of the system, with a particular emphasis on its suitability for commuter riders. The study considered 25 factors that may influence the user’s satisfaction with water metro. Using machine learning techniques, a predictive model was developed for identifying the influencing factors on the passengers’ overall satisfaction of the Kochi water metro system. The study revealed that the water metro fare aligns with passenger expectations and identified water metro awareness as a key factor among other factors. Additionally, the random forest machine learning model was found to be the most effective for predicting overall passenger satisfaction with the Kochi water metro. The study findings help the policymakers and operators to prioritize the improvement areas for increasing the water metro ridership.