Slash pine (Pinus elliottii Engelm) is the second most important commercial species in the southeastern United States, it is usually established in poorly drained flatwoods where it outperforms other common commercial pine species. Modeling slash pine growth and how it responds to silvicultural treatments is of interest to forest managers wanting to maximize their investments in the region. In this research, a system of differential equations is proposed to model slash pine growth including the effect of silvicultural treatments (i.e., bedding, and vegetation control). Data for this model came from a long-term study (30 years) established by the Plantation Management Research Cooperative (PMRC) across Georgia, Florida, and South Carolina.To construct this growth and yield system, a dominant height model was first proposed in which the effect of bedding and vegetation control was closely evaluated. This model guided the construction of the mortality model, in which a modeling approach including height increments instead of time increments when using differential equations was evaluated. Building upon the mortality model, the whole system of differential equations was proposed. The model system describes the trajectory of the three state variables: dominant height, survival/mortality, and basal area. Treatments effect was incorporated to the dominant height and basal area models by using parameter modifiers and dummy variables associated with each one of the treatments. Survival was not affected by the studied treatments, but the presence of fusiform rust was found to be essential to determine the stand density trajectories for the evaluated stands. The parameter for the growth and yield system were estimated simultaneously using maximum likelihood and the variance/covariance was modeled within the system. The use of stochastic differential equations applied to these types of models in forestry was evaluated and summarized in the last part of this research.