Evapotranspiration is an important part of the hydrological cycle and a key indicator to measure hydrological and energy transfer in the soil-plant-atmosphere continuum (SPAC). In this study, maize farmland in the lower Yellow River, an important grain production base in China, was selected as the research object. Based on the actual observation data of the eddy covariance system during the summer maize growth cycle, ten common evapotranspiration estimation models, including the FAO-56 Penman‒Monteith (P-M) model, Hargreaves–Samani (H-S) model, Priestley–Taylor (P-T) model, Makkink (Ma) model, Jensen–Haise (J-H) model, Irmark–Allen (I-A) model, Doorenbos–Pruitt (D-P) model, McCloud (Mc) model, Kimberly–Penman (K-P) model and Abtew (Ab) model, were evaluated in estimating the applicability of the actual evapotranspiration. The mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE) and index of agreement (D) were chosen as evaluation indices. The Pearson correlation test and principal component analysis methods were used to explore the main influencing factors of actual evapotranspiration. The comprehensive ranking of the applicability of each model in the study area was obtained by synthesizing each index: J-H > P-T > Mc > K-P > I-A > P-M > D-P > Ab > Ma > H-S. it could be concluded that the J-H model was the most suitable in the study area, followed by the P-T model, while the H-S model attained the worst simulation performance. The evapotranspiration of summer maize at the tasseling-milky maturity stage in this region was the highest, and the solar radiation, net radiation and photosynthetically active radiation exhibited a strong correlation with evapotranspiration and greatly impacted evapotranspiration. This study plays an important role in the development of efficient water-saving agriculture, irrigation forecasting and sustainable utilization of water resources in the core area of grain production in China.