Abstract: Fruit number per plant (FNP) is an important yield component of tomato plants. To quantitatively analyze the relationship between FNP of different protected tomato varieties and local environmental conditions, field experiments were carried out in Suoshi Village, Nanjing, in 2009, 2010, and 2011, respectively, involving tomato varieties and fertilizer and water uses. The "American mole 1" (B1, early maturing), "Chaoshijifanqiedawang" (B2, late maturing), and "American 903" (B3, medium maturing) tomato varieties were adopted as experimental materials in the study. In accordance with the processes of dynamic balance and self-regulation of buds, flowers, and fruit number per plant of various protected tomatoes varieties, the flower and fruit abscission number, bud number per plant, and FNP models were built by analyzing the relationships among the number of bud, flower abscission, fruit abscission, FNP, and local environmental factors. The effects of temperature, light, nitrogen, and water were introduced into the developed models. The models were validated using independent experimental datasets. The results showed the root mean squared error (RMSE), mean absolute error (X_de), and determinant coefficient (R₂) for the simulated and measured values of bud number per plant to be 2.452 (n=24), 1.851, and 0.976 for B1; 1.820 (n=24), 1.422, and 0.948 for B2; and 1.849 (n=24), 1.464, and 0.949 for B3; respectively. Also the RMSE, X_de and R₂ for flower abscission number per plant were 0.712 (n=16), 0.662, and 0.786 for B1; 0.730 (n=17), 0.662, and 0.965 for B2; and 1.229 (n=16), 1.091, and 0.952 for B3; respectively. The RMSE, X_de, and R₂ for fruit abscission number per plant were 0.391 (n=15), 0.342, and 0.849 for B1; 0.439 (n=15), 0.346, and 0.966 for B2; and 0.318 (n=15), 0.288, and 0.961 for B3; respectively. Then the RMSE, X_de, and R₂ for FNP were 0.839 (n=27), 0.712, and 0.934, respectively. It was noted that the simulated values agreed well with the measured ones. This suggested that FNP of different protected tomato varieties under different water and fertilizer conditions were well simulated by the developed models in this study.