This work aimed at investigating the heuristic potential of a process-based model of peach fruit expressing seasonal changes in several quality attributes of fruit (e.g., size, percentages of flesh, water, sugar and acid contents) and fruit sensitivity to brown rot (skin density of cracks). Firstly, we showed that this “Virtual Fruit” could be used to analyze the impact of a single mutation which decreased the fruit’s requirement for carbon on peach fruit behavior. The mutation triggered large effects on several variables of the fruit development model (growth, respiration and metabolism) and delayed the fruit developmental rate. Such a virtual approach could lead to new ways of exploring the impact of mutations, or naturally occurring genetic variations, in silico, under different environmental conditions. Secondly, we illustrated how the “Virtual Fruit” could be possibly used to design peach ideotypes with high fruit mass and sweetness and low skin density of cracks. Since these traits are antagonists, we treated this design as a multi-objective optimization problem. An evolutionary algorithm was applied to solve this multi-objective optimization problem based on the “Virtual Fruit”. The optimized variables were six genetic parameters of the “Virtual Fruit”. This optimization procedure provided a large diversity of solutions (ideotypes). Ideotypes with low fruit mass had a high sweetness and low skin density of cracks. In a current breeding scheme, fruit mass would be the only criterion, but alternative schemes could be considered for the future, favoring organoleptic quality or environment friendly practices, or more generally, aiming at finding acceptable trade-offs between several criteria. In this case, modelling and model-based optimization would be helpful.