Most cancer models focus on the growth and progression of a tumor once a neoplasm has first formed. This work focuses on building a mathematical model of the early initiation processes for the earliest neoplasm for lung adenocarcinomas induced by smoking. The biology was triaged to identify the key biological behaviors causing the phenotype transition from never-smoker lung cells to the earliest phenotype considered a neoplasm. The biology is then translated into a set of nonlinear ordinary differential equations (ODEs). Finally, constrained optimization is used to obtain a single set of model parameters that simultaneously provides a good fit to all the experimental data sets and accurately reproduce the key biological phenomena, without producing any unacceptable one.