Process-based plant models are increasingly used in agricultural research over the last decades, and are undoubtedly interesting tools which allows quantifying plant responses to environmental factors within a mathematical framework. The purpose of theses approaches is to improve (i) understanding of key physiological processes that determine whole-plant behavior and fruit quality, and (ii) characterization of phenotypes plasticity. Environmental factors are often considered as model-driving variables, and plant- or genotype-specific coefficients are used to represent physiological characteristics. As a result, these models can offer significant advantages in assessing and predicting the effects of climate change as compared to purely statistical or rulebased ones based on previously collected data. More recently, process-based models combined to genetic approaches have also been shown to provide a relevant framework for analysing genetic diversity of complex traits and enhancing progress in plant breeding for various environments. Indeed if the models adequately describe the effects of the genetic variability in a few climatic scenarios, they can be extended to a much larger number of scenarios in order to evaluate the comparative advantage of a given allele in different hypothetical environments associated with climate change. Such an approach provides a way of overcoming the uncertainties associated with gene and environment context dependencies that currently impeded the progress of molecular breeding. Models integrating physiological processes and their genetic control will form the first step to design and test in silico plants for future environments. In grapes, modeling plant abiotic stress tolerance and fruit quality is still a challenging issue. An overview of the present knowledge and main process-based models in literature dealing with this topic will be presented. Models developed for phenology, plant drought response and berry sugar accumulation will be outlined. These models consist of simple responses curves for one trait or are able to simulate more complex physiological processes. Genetic parameters were defined and their variations among genotypes or segregating populations analysed. The potential use of such models to simulate ideotype behavior under future climatic conditions will also be discussed.