Curling is a strategic ice sport that presents unique challenges for AI research due to its combination of complex decision-making and intricate physical dynamics. This project aims to develop a physics-based curling simulator to address these challenges, enabling accurate modeling of stone movement, ice conditions, and sweeping effects. Our approach involves utilizing an existing physics engine, MoJuCo, to simulate realistic curling interactions. We implemented physics models based on leading theories for basic curling shot selections. The simulator initially focuses on stone dynamics and shot selection, with more complex features such as sweeping effects being added in later iterations. A visualization web app displays shot outcomes and will eventually support AI training and data analysis.In addition to the simulation application for curling research, we developed a training module for both the physics of curling and interacting with the MoJuCo library. This module is designed to help new student learn about the complicated physics of curling. This module also helps students learn how to implement and maintain MuJuCo based features into the simulator.