To achieve the automation of blast furnace operation, an automatic control system for hot metal temperature (HMT) was developed. Nonlinear model predictive control (NMPC) which predicts up to ten-hour-ahead HMT and calculates appropriate control actions of pulverized coal rate (PCR) was constructed. Simulation validation showed that the NMPC algorithm generates control actions similar to those by the operators and that HMT can be maintained within ±10 °C of the set point. The automatic control system using NMPC was then implemented in an actual plant. As a result, the developed control system suppressed the effects of disturbances, such as the changes in the coke ratio and blast volume, and successfully reduced the average control error of HMT by 4.6 °C compared to the conventional manual operation. The developed control system has contributed to the reduction of reducing agent rate (RAR) and CO2 emissions.