This paper investigates feasibility of developing a predictive rating method to optimize line rating of underground transmission lines based on weather forecast information. Transmission lines, overhead or underground, are essential and indispensable parts of the electric grid which basically transfer energy from the production point to where it is needed. Line rating defined as line's maximum capacity to transfer electric current and power safely and reliably under certain constraints and criteria. To ensure safe operation, rating has been classically calculated according to the worst case scenario, where conductor's temperature rise would remain within specified limit under most unfavorable conditions. Obviously, such an approach leads to very conservative results, leaving line mostly underutilized throughout its life span. In order to optimize line utilization, ambient adjusted rating and more recently dynamic line rating methods are developed. For instance, in dynamic line rating, real-time data are used to determine instantaneous line rating. We have investigated necessity and possibility of developing a predictive model for underground transmission lines by employing weather forecast information, which would enable line operators or owners to anticipate optimized line ampacity and maximum rating over the next few days. The proposed basic model builds upon the already developed and well-documented analogy between thermal and electrical circuits, yet incorporates a time varying source to account for constantly changing ambient temperature. Deterministic weather forecast information can be collected from Environment Canada.