The Northeast China cold vortex (NCCV) during late summer (from July to August) is identified and classified into three types in terms of its movement path using machine learning. The relationships of the three types of NCCV intensity with atmospheric circulations in late summer, the sea surface temperature (SST), and Arctic sea ice concentration (SIC) in the preceding months, are analyzed. The sensitivity tests by the Community Atmosphere Model version 5.3 (CAM5.3) are used to verify the statistical results. The results show that the coordination pattern of East Asia-Pacific (EAP) and Lake Baikal high pressure forced by SST anomalies in the North Indian Ocean dipole mode (NIOD) during the preceding April and SIC anomalies in the Nansen Basin during the preceding June results in an intensity anomaly for the first type of NCCV. While the pattern of high pressure over the Urals and Okhotsk Sea and low pressure over Lake Baikal during late summer—which is forced by SST anomalies in the South Indian Ocean dipole mode (SIOD) in the preceding June and SIC anomalies in the Barents Sea in the preceding April—causes the intensity anomaly of the second type. The third type is atypical and is not analyzed in detail. Sensitivity tests, jointly forced by the SST and SIC in the preceding period, can well reproduce the observations. In contrast, the results forced separately by the SST and SIC are poor, indicating that the NCCV during late summer is likely influenced by the coordinated effects of both SST and SIC in the preceding months.