MOOSE is a parallel computational framework designed to solve coupled systems of nonlinear equations, particularly in nuclear simulations. It is based on the Jacobian-free Newton-Krylov (JFNK) method, which allows for efficient solution of large nonlinear systems without explicitly forming the Jacobian matrix. MOOSE uses a modular architecture, enabling the addition of new physics through "Kernels," which are mathematical operators representing specific physical processes. This modular design allows for flexible coupling of different physics and efficient handling of nonlinear material properties and boundary conditions. MOOSE leverages the libMesh finite-element framework for parallel computations, providing a flexible environment for solving complex multiphysics problems. The framework supports a wide range of advanced capabilities, including dimensionless physics, massively parallel computation, arbitrary order finite elements, higher-order time integration, and mesh adaptation. These features work together seamlessly, allowing application developers to focus on defining the residual in the form of a Kernel. Several applications are currently being developed using the MOOSE framework, including BISON for reactor fuel performance modeling and PRONGHORN for pebble bed reactor simulations. These applications demonstrate the effectiveness of MOOSE in handling complex, coupled systems of equations. Additionally, a multi-group neutron diffusion simulation has been developed using MOOSE, validated against the PBMR400 benchmark. MOOSE combines JFNK, physics-based preconditioning, and a flexible pluggable architecture to enable efficient and accurate multiphysics simulations. This framework allows for rapid prototyping and the development of production-ready, massively parallel codes, significantly reducing the time required for such simulations. The advanced capabilities of MOOSE, such as error estimation and adaptivity, further enhance the accuracy and efficiency of engineering simulations.MOOSE is a parallel computational framework designed to solve coupled systems of nonlinear equations, particularly in nuclear simulations. It is based on the Jacobian-free Newton-Krylov (JFNK) method, which allows for efficient solution of large nonlinear systems without explicitly forming the Jacobian matrix. MOOSE uses a modular architecture, enabling the addition of new physics through "Kernels," which are mathematical operators representing specific physical processes. This modular design allows for flexible coupling of different physics and efficient handling of nonlinear material properties and boundary conditions. MOOSE leverages the libMesh finite-element framework for parallel computations, providing a flexible environment for solving complex multiphysics problems. The framework supports a wide range of advanced capabilities, including dimensionless physics, massively parallel computation, arbitrary order finite elements, higher-order time integration, and mesh adaptation. These features work together seamlessly, allowing application developers to focus on defining the residual in the form of a Kernel. Several applications are currently being developed using the MOOSE framework, including BISON for reactor fuel performance modeling and PRONGHORN for pebble bed reactor simulations. These applications demonstrate the effectiveness of MOOSE in handling complex, coupled systems of equations. Additionally, a multi-group neutron diffusion simulation has been developed using MOOSE, validated against the PBMR400 benchmark. MOOSE combines JFNK, physics-based preconditioning, and a flexible pluggable architecture to enable efficient and accurate multiphysics simulations. This framework allows for rapid prototyping and the development of production-ready, massively parallel codes, significantly reducing the time required for such simulations. The advanced capabilities of MOOSE, such as error estimation and adaptivity, further enhance the accuracy and efficiency of engineering simulations.