Atmospheric rivers are long, narrow pathways in the troposphere that play an important role in transporting atmospheric moisture to different regions of the world. When accompanied by favorable synoptic and thermodynamic conditions, they can cause heavy rainfall or flooding in the affected areas. In this study, an approach based on the THR image processing algorithm in the IPART Python package was used to identify atmospheric rivers entering the Lake Urmia Basin, and the relationship between extreme precipitation events during the rainy months (November to April) and atmospheric rivers in the 1991–2020 period was statistically analyzed. The results showed that during this period, 288 atmospheric rivers crossed the Lake Urmia Basin. The highest frequency occurred in April (32.64%) and March (26.74%), with the main sources being the Mediterranean Sea (33.68%), the Red Sea (17.71%), and the Gulf of Aden (13.89%). On average, atmospheric rivers contributed 16.9% to the total number of extreme precipitation events in the studied months, with the highest contribution (25.8%) occurring in April. At the station scale, November at Sarab Station showed the highest effect in terms of the number of extreme precipitation events (27.5%), while March at Mahabad Station had the highest effect in terms of the total amount of extreme precipitation. The approach used in this study can be applied to develop extreme precipitation risk maps and to predict extreme precipitation events and floods.