Abstract: In order to optimize the climate management for pot planted poinsettia (Euphorbia pulcherrima Willd.) grown in a greenhouse, a model of pot planted poinsettia growth and development simulation was developed. Experiments with different planting dates and densities were conducted in a multi-span Venlo type greenhouse of Nanjing. The photo-thermal effects on the development and growth of poinsettia were quantitatively analyzed using the experimental data. Based on the quantitative analysis, a sub-model for predicting the development stages of poinsettia was developed using an integrated photo-thermal index physiological product of thermal effectiveness and PAR, PTEP. A sub-model for predicting the dry matter production and dry matter partitioning of poinsettia was developed using the canopy intercepted PTEP, PTEPint. A growth and development simulation model for pot planted poinsettia was developed by integrating the two sub-models mentioned above. Independent experimental data were used to validate the model. The results showed that the model could give predictions of the development stages, dry matter production, and organ dry weight of poinsettia crops satisfactorily. Based on the 1:1 line, the determination coefficient (R2) between the predicted and observed development stages is 0.99; and the root mean squared errors (RMSE) between the predicted and observed days from pinching to start of short day treatment, first visible cyathia, first visible bud, third visible bud and flowering date are, respectively, 0.7, 3, 3.5, 0.7 and 2 days. Based on the 1:1 line, the R2 and RMSE are 0.98 and 7.12 g/m2, for total biomass production, 0.97 and 7.49 g·m-2, respectively, for leaf dry weight, 0.91 and 3.89 g/m2, respectively, for stem dry weight, 0.95 and 2.48 g·m-2, respectively for cyathia dry weight. The model developed in this study gives more accurate predictions for development stages than the growing degree days (GDD) based model (with RMSE of 8, 4.5, 3.8, 2.8 and 7.2 days, respectively) does, and gives significantly higher prediction accuracies for total biomass production than the photosynthesis driven crop growth model (with R2 and RMSE of 0.77 and 35.06 g/m2, respectively) does. Based on the results obtained in this study, it can be concluded that the model developed in this study can give satisfactory predictions of pot planted poinsettia development and growth, hence, can be used for decision making for precision control of light and temperature in greenhouse poinsettia production.