This paper introduces a system designed to assist a public transport operator, in identifying services requiring reinforcement, predicting or detecting service bunching, and refining schedules based on historical data analysis. In routes with low frequency, the system analyzes factors such as occupancy, punctuality, punctuality trend, and the percentage of completed routes to generate a prioritized list of services that could benefit from additional vehicles for reinforcement. For high-frequency routes, the system examines the distances between consecutive vehicles and their behavior to identify groups of services that may result in bunching scenarios. Furthermore, a regression study is conducted to uncover punctuality patterns that may necessitate a reevaluation of official schedules.