Breast cancer is the most common cancer among women as it accounts for about 25% of all female cancer cases. Studies have shown that early detection of breast cancer increases the chances of a positive prognosis amongst patients therefore it is crucial to provide accurate diagnosis tools in routine exams. Experimenting with new techniques and tools that can provide increased accuracy requires time-consuming and costly studies, therefore, simulating outcomes that have high potential can provide guidance for increased accuracy without requiring expensive tests. This project outlines the possibility of developing an advanced anthropomorphic mesh phantom of the breast to experiment different contrast agents with. The phantom would contain all the components of a real breast and it would be able to simulate the physiological and metabolic components that play a role in the outcome of a real tomosynthesis-mammography scan. This project focuses on creating a basic model of a breast and a tomosynthesis system that provides an indication on whether a simulation system can be produced. The materials used for this project include Abaqus/CAE software, Python, MCNP6.2, and scripting tools as well as resources on tomosynthesis equipment. The results demonstrated a positive outcome thus indicating that the model can be further developed to incorporate the multiple components of a real breast scan to increase the simulation’s realism. Further work on this project will focus on increasing the model’s complexity and incorporating contrast agents so that the efficacy of each can be explored.