Northeast China belongs to one of the most vulnerable regions to climate change in China, with its lake system experiencing significant impacts. Consequently, a comprehensive investigation of the phenological characteristics of lake ice in Northeast China holds paramount scientific and application value. This study selected 31 lakes exceeding an area of > 20km2 in Northeast China, and merged MOD11A1 and MYD11A1 data via Google Earth Engine (GEE) to establish a time series of lake surface temperatures (LST). The orthogonal distance regression algorithm was employed to fill in missing values, resulting in a constructed lake surface temperature series for Northeast China. The dataset presents lake surface temperatures and lake ice phenology of 31 selected lakes spanning from 2000 to 2022. The lake ice phenology included freeze-up date (FUD), break-up date (BUD), and ice cover duration (ICD). Additionally, 28 weather stations were selected for verification, demonstrating high accuracy with R2 values of 0.979 and 0.988 for LST, ground surface temperature (GST), and air temperature (AT), respectively. The statistical results of ice conditions based on hydrological yearbooks verify lake ice phenology, with R2 values of 0.875, 0.852, and 0.938 for icing day, melting day, and ice period, respectively. These findings affirm the dataset's reliability, offering valuable support for research on spatiotemporal changes in ice cover and climate change in Northeast China.