Evapotranspiration (ET) plays an important role in restoring stormwater retention capacity of bioretention systems and improving microclimate conditions in urban areas. However, there is still a lack of applicable methods to accurately predict ET from bioretention systems. In this study, the applicability of five commonly used models (i.e., ASCE Penman-Monteith, Priestley-Taylor, Penman, Hargreaves, and Blaney-Criddle) in predicting ET from bioretention systems was assessed based on lysimeter measurement data from a field-scale bioretention system located in Beijing. The measured average daily ET from the bioretention system using a lysimeter is 2.24 mm·d−1. ET from the bioretention system is significantly related to solar radiation, vapor pressure deficit, and air temperature (p < 0.001). The ASCE Penman-Monteith, Priestly-Taylor, Penman, and Blaney-Criddle models underestimate average daily ET by 23.31%, 18.50%, 18.93%, and 29.60%, respectively. However, the Hargreaves model overestimates ET by 35.13%. Incorporating various crop coefficients in different plant growth stages can significantly improve the accuracy of these five models. The Penman model is demonstrated to be the most accurate in predicting ET from the bioretention system, followed by the Priestly-Taylor, and ASCE Penman-Monteith models. These three models have relative errors ≤2.68%, RMSE ≤0.66 mm·d−1, R2 ≥0.92, and NSE ≥0.95. The Hargreaves or Blaney-Criddle models could not accurately predict ET from the bioretention system because solar radiation is not considered in these two models. The results provide references for selecting and implementing models to predict ET from bioretention systems.