ABSTRACT The HortSyst model is a new discrete time model for describing the dynamics of photo-thermal time (PTI), total dry matter production (DMP), N uptake (Nup), leaf area index (LAI), and evapotranspiration (ETc) for greenhouse crops. The first three variables are considered as state variables and the latter two are conceptualized as output variables. This model was developed as a tool for decision support systems in Mexican greenhouses for the application of N and water in tomato (Solanum lycopersicum L.) production. The HortSyst has 13 parameters. It was used to calibrate the model and estimate the correct parameter values for the crop season. An experiment was carried out to test model predictions in a greenhouse during the autumn-winter season in Chapingo, Mexico. Tomato ‘CID F1’ was grown in a hydroponic system and plants were distributed with a density of 3.5 plants m-2. The tomato crop was transplanted on 21 August 2015. A weather station was installed inside the greenhouse to measure temperature, relative humidity, and global radiation. The HortSyst model provides an excellent predictive quality for DMP, Nup, LAI, and ETc according to the statistics. Values for bias (BIAS) were DMP (-3.897), Nup (-0.071), LAI (0.026), and ETc (3.647), values for root mean square error (RMSE) were DMP (14.543), Nup (0.500), LAI (0.100), and ETc (39.330), and values for modeling efficiency (EF)were DMP (0.996), Nup (0.991), LAI (0.998), and ETc (0.815). The model proposed and described in this paper can be integrated as a decision support tool for N supply and irrigation management in greenhouse production systems.