Abstract: Systems and methods for modeling a temperature in a thermal package in a lane of commerce using forecast weather data or estimating the actual temperature history in a thermal package using actual weather data. Lane temperature is recognized and used as an intermediate calculated variable derived from weather data. Machine learning techniques estimate the lane temperature to determine a model. Product temperature in thermal packaging is estimated by simultaneously solving a set of heat transfer equations. The above is used to with forecast weather data to calculate a lane temperature and then calculate an expected product temperature based on the time and date of shipment. This product temperature curve is then analyzed with a set of decision rules to improve decision making on when to make a shipment and the best packaging to use.