The fabrication of functional tissue-engineered cardiovascular implants remains a significant challenge in regenerative medicine, necessitating deep understanding of the biological mechanisms that drive maturation. While biohybrid implants based on textile scaffolds provide essential structural support, the eventual mechanical success of these implants depends on mechanobiological adaptation. We developed a thermodynamically consistent computational framework to predict tissue evolution and mechanical response during the in vitro cultivation process. Our approach introduces a stress-driven homeostatic surface to describe volumetric growth and fiber reorientation, coupled with an energy-based approach to model collagen densification during the maturation process. To apply our model to biohybrid implants, we incorporate anisotropic scaffold reinforcement using structural tensors. The model was validated using experimental data. It was subsequently applied to various numerical examples, specifically focusing on the maturation of tissue-engineered vascular grafts (TEVGs) and tissue-engineered heart valves (TEHVs). The primary objective is to utilize these in silico experiments to optimize material design and mechanical loading conditions throughout the cultivation process. In silico trials revealed that biological adaptation often overrides the predefined anisotropy of the scaffold; collagen density and alignment adapt to maintain stress homeostasis regardless of the starting architecture. Global sensitivity analysis reveals that by the conclusion of the cultivation process, growth and remodeling parameters have a dominant influence on the overall stress response, overtaking the contributions of the initial scaffold properties. Furthermore, the model identifies tissue contractility during TEVG maturation as a critical driver of fiber alignment toward the axial direction. This suggests that tailoring loading protocols or adjusting scaffold compliance could help in achieving native-like architectures. These results demonstrate the potential of the proposed model to improve experimental designs and explain factors contributing to the current discrepancies between in vitro and in situ outcomes.