Yield monitor data is widely accepted as a valuable tool within the agricultural industry when making agronomic, financial, and management decisions and has been inaugural in the establishment of precision agriculture. Automation and sophistication of processes involved with yield monitoring systems has modernized farming through increased precision and efficiency. Traditional elevator mount mass-flow yield monitors are vulnerable to error due to insufficient calibrations and material flow inconsistencies resulting from threshing and separating processes. An advanced interconnected system that is able to autonomously analyze and adjust the mass-flow sensor calibration curve based on real-time data from the combine harvester has the potential to reduce error in comparison to traditional yield monitoring systems that require manual calibration of the mass-flow sensor. The accuracy of estimated yield using a traditional mass-flow yield monitoring system requiring manual calibration of the mass-flow sensor was compared with a yield monitoring system capable of autonomous mass-flow sensor calibration. A John Deere S790 combine harvester and grain cart with weigh scales threshed and weighed Triticum aestivum Linnaeus. The parameters examined were grain kernel moisture content, temperature, and weight of crop harvested with time. The weights of the harvested grain estimated by the respective calibration systems were compared to the weight measured in the grain cart for evaluation of yield accuracy and converted to bushels per acre for analysis. The average accuracy for the autonomous mass-flow sensor calibration system was 97.8% when compared with the average accuracy for the manual calibration yield monitoring system of 94.4%.