It is well known that physical activity plays a key role in maintaining good health. Over the past few decades, there has been a significant increase in both the number of fitness centres worldwide and the number of individuals who use them. In addition to contributing to public health, fitness centres also play an important role in the economy, generating revenue by attracting new members and retaining existing ones. During peak hours, however, the number of customers present in a facility often exceeds the available equipment capacity. As a result, some customers are forced to wait for equipment to become available or to deviate from their planned workout routines, which can lead to dissatisfaction and member attrition. In this paper, we propose a decision support optimization model designed to reduce peak-hour congestion in fitness centres while improving customer experience. The model is intended to support an online booking system in which customers submit provisional workout plans along with their preferences. The system then outputs a final, congestion-free workout plan for each customer that closely matches these preferences. The proposed model aims to maximize equipment utilization while ensuring that each customer can complete their workout with minimal idle time. The model is tested on realistic data sets, and the computational results show that, in addition to supporting the proposed booking system, it can reduce customer idle time by up to 19% compared to a first-come, first-served operational policy.