The energy grid relies on a dependable transmission system to traverse electricity across miles through plains, mountains, and cities. The grid is in a continuous state of expansion and older lines are expected to operate for decades longer than their originally anticipated lifespan when they were installed. Each line is exposed to many different environmental modalities that cause the integrity of the line to erode. Animals, fungi, moisture and air, storms, hurricanes, car crashes, and the strain of the loaded lines all affect the transmission line’s states of degradation. Knowing how and when to replace these lines is paramount to keeping a reliable energy system functional. While the transmission system has many components that are required to perform well to keep energy flowing across the lines, there are two parts that have the most detrimental consequences, given their failure. The pole or structure and the conductor are the foundation of the transmission line and require the most attention at their demise. Repairs and replacements are heavily dependent on the budget of the utility company. The goal of this thesis is to develop analytical models that support maintenance and replacement decisions for overhead transmission lines. In collaboration with a local utility company, we develop data-driven and physics-informed predictive models for degradation of overhead transmission conductors due to environmental and operational conditions. Additionally, we develop time-based and condition-based maintenance strategies for treatment and replacement of utility poles under budget limitation using integer programming and Markov decision processes, respectively.