Smart indoor parking management systems represent an evolution of traditional parking setups. These systems provide real-time information to users, simplifying the search for available parking spots, while also giving operators the ability to monitor and control the system remotely. This research aims to apply queuing theory principles to model parking system dynamics. By implementing a queuing system model, arrival and service times can be predicted through detailed analysis and calculation. Additionally, a Graphical User Interface (GUI) is developed and integrated into the parking system, allowing operators to monitor parking lot status and view key statistics, such as arrival rates and service times. The GUI also enables parking reservations through manual control of parking inputs and outputs. Currently, most parking systems provide limited information, often requiring users to manually search for open spots. This research seeks to support parking operators in designing efficient systems that increase revenue while enabling convenient remote management, ultimately offering users a time-saving, stress-free parking experience.