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In this paper we tackle the overbooking problem in hotel revenue management (RM). We propose a simulations-based approach for the overbooking problem. It is based on accurately estimating all the hotel's processes, such as reservations arrivals, cancelations, length of stay, demand seasonality, etc. Subsequently, all these processes are simulated forward in time in a Monte-Carlo fashion. The optimal overbooking limit is selected as the one that will give the targeted denied ratio. Our model is designed to handle the time dependent nature of the dynamics of cancellations and reservations, and is therefore very realistic, as it does not rely on simplifying analytical assumptions. To test our approach, we considered as a case study the problem of designing an overbooking strategy for Plaza Hotel, Alexandria, Egypt. The results demonstrate the effectiveness of the proposed approach.