The objective of this study was to develop an empirical model for whole-plant net photosynthetic rate (P_n, μmol s^-1 per plant) as a function of four essential environmental factors: photosynthetically active radiation (PAR) above the canopy (I, W m^-2), air temperature (T, ℃), CO₂ concentration (C, μmol mol^-1), and vapor pressure deficit (VPD, kPa) by using the dataset of P_n and corresponding environmental factors. To prepare the dataset, we monitored the photosynthesis of mature cherry tomato plants grown in a commercial greenhouse for 15 days in summer with a non-contact, non-intrusive photosynthesis real-time monitoring chamber. Four linear models, namely the general linear model (G-model), linear interaction model (I-model), linear squared model (S-model), and linear interaction-squared model (IS-model), were developed and validated their accuracy. The results suggest that the proposed models successfully simulated the cherry tomato plant's photosynthesis grown in a commercial greenhouse, and IS-model kept relatively higher accuracy regardless of weather conditions. However, to achieve the most accurate P_n estimation is to apply S-model for a sunny day and I-model for a rainy day. These models are prospective for a model-based plant diagnosis to make a judgment whether the current photosynthesis is normal or not.