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Cellular signaling and dynamic interaction among genes result in stable phenotype structures such as tumor or non tumor cells. Tumor and non-tumor cellular cells often contain some identical cancer causing genes but due to differences in their regulatory networks they evolve differently. As a result, if such regulatory networks are discovered one could predict whether a cell containing particular cancer genes will in fact end up to become a cancerous cell. This paper utilizes a mathematical approach to determine such regulatory rules for a set of cells containing cancer causing genes and uses computer simulation to predict whether in a long run a particular cell will evolve into a cancerous cell. The proposed process utilizes Probabilistic Boolean Networks (PBN) on two gene regulatory networks; one for tumor and one for non-tumor producing structures. The process uses a regression analysis to identify the regulatory networks and a computer simulation model to predict long term cancer potential.