This achievement is the output of a joint research project titled Seasonal Prediction of Agricultural Drought Risk for Iran Based on Statistical (Machine Learning)-Dynamical Climate Model, conducted with the support of the Iran National Science Foundation (INSF) and the National Natural Science Foundation of China (NSFC). The project was jointly led by Dr. Peyman Mahmoudi (faculty member at USB) and Prof. Jing Yang (from Beijing Normal University). The expert team of this project included Dr. Pouria Jafari, Dr. Alireza Ghaemi, and Dr. Fatemeh Firoozi from Iran, alongside Prof. Jin Jian and Prof. Qing Bao from prestigious Chinese scientific institutions. In addition to the publication of 8 prestigious international papers (5 Q1 and 3 Q2 articles), the scientific achievement of this research includes the launch of an operational system that generates and publishes three new sets of forecast maps every month. These continuous and regularly updated outputs include: the Meteorological Drought Outlook (SPI-1), the Vegetation Anomaly Outlook (NDVI), and the Agricultural Risk Outlook, which classify risk levels to assist farmers and managers in precise planning. Interested individuals can visit the project platform at https://meteonex.hkust.edu.hk/products to view these monthly predictions.