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Basic greenhouse is a kind of primary greenhouse without operation equipment. At present, more than 90% of greenhouse in China belongs to basic greenhouse. In order to solve the problem of evapotranspiration simulation in basic greenhouse, Penman-Monteith (PM) model, which is the most widely used mechanism model in greenhouse, was used to simulate the evapotranspiration in basic greenhouse. Bayesian method was used to estimate the parameters and analyze the uncertainty of six PM models composed of two key parameters ra (aerodynamics resistance) and rc (canopy resistance). Three precision indexes, namely mean relative error (MAE), determination coefficient (R2) and Wilmot consistency index (D), were used to evaluate the model accuracy for the model calibration year (2018) and test year (2019). The results showed that the Bayesian parameter estimation method made the PM evapotranspiration model with high accuracy in the basic greenhouse day scale estimation, and five of the six PM models met the three accuracy indexes in the model calibration year and model test year. The Bayesian parameter estimation method can effectively reduce the uncertainty of some parameters in the basic greenhouse day scale PM model. In the model ra2-rc3, the posterior distribution interval of parameter a2 was reduced by 97.65%, 92.38%, 93.31% and 98.24%, respectively in the four growth stages compared with the prior distribution interval. In the model ra2-rc2, the posterior distributions interval of parameters D50, KQ, Q50 and gmax were reduced by 96.44%, 56.08%, 97.78% and 99.75%, respectively compared with the prior distribution interval. Two PM models suitable for daily scale evapotranspiration simulation of basic greenhouse were screened out: ra2-rc3 and ra3-rc3, the optimal model was ra2-rc3. The research result can provide theoretical basis for improving crop irrigation and water use efficiency in basic greenhouse.