Frequency aging is an important factor in frequency standards. Aging is the portion of frequency drift that is intrinsic to the frequency standard. Improving the knowledge surrounding the mechanisms of aging provides means to minimize their impact. To study frequency aging further, several known models used to describe frequency aging were investigated. A set of oven-controlled oscillator datasets were obtained in order to evaluate two frequency aging models. The first model is a logarithmic model, which was selected due to its ubiquity. The second model is a linear Kalman Filter model, which was chosen for its dynamic capabilities. The results of each modeling procedure were analyzed using linear frequency aging baseline comparison, coefficients of determination, and residual analysis. It was determined that the linear Kalman Filter model provides better model fidelity than the logarithmic model. Additionally, the analysis found that the linear frequency aging baseline comparison and residual analysis provide a sufficient comparison suite, with the coefficient of determination adding little in terms of further insight.