Computational methods are presented for modeling the catalytic center of an enzyme and calculating the energy associated with given molecular geometry. First, an introduction to general theory is given, including a brief discussion of quantum mechanics (QM), molecular mechanics (MM), and hybrid QM/MM, a standard approach that divides the system into a region requiring a description of the electronic structure (QM) and a remainder that can be considered a perturbation (MM) to the system. Next, the nitrogenase enzyme will be used as a sample system to explain in detail how modeling is carried out. This discussion will review the broken symmetry (BS) approach within DFT, a computational approach that describes the spin states of multiple Fe centers. The review concludes with a discussion of machine learning (ML) and the training of a neural network (NN) potential based on QM calculations.