Mechanical properties of three-dimensional (3D) scaffolds can be appropriately modulated through novel fabrication techniques like 3D fiber deposition (3DF), by varying scaffold’s pore size and shape. Dynamic stiffness, in particular, can be considered as an important property to optimize the scaffold structure for its ultimate in vivo application to regenerate a natural tissue. Experimental data from dynamic mechanical analysis (DMA) reveal a dependence of the dynamic stiffness of the scaffold on the intrinsic mechanical and physicochemical properties of the material used, and on the overall porosity and architecture of the construct. The aim of this study was to assess the relationship between the aforementioned parameters, through a mathematical model, which was derived from the experimental mechanical data. As an example of how mechanical properties can be tailored to match the natural tissue to be replaced, articular bovine cartilage and porcine knee meniscus cartilage dynamic stiffness were measured and related to the modeled 3DF scaffolds dynamic stiffness. The dynamic stiffness of 3DF scaffolds from poly(ethylene oxide terephthalate)-poly(butylene terephthalate) (PEOT/PBT) copolymers was measured with DMA. With increasing porosity, the dynamic stiffness was found to decrease in an exponential manner. The influence of the scaffold architecture (or pore shape) and of the molecular network properties of the copolymers was expressed as a scaffold characteristic coefficient α, which modulates the porosity effect. This model was validated through an FEA numerical simulation performed on the structures that were experimentally tested. The relative deviation between the experimental and the finite element model was less than 15% for all of the constructs with a dynamic stiffness higher than 1 MPa. Therefore, we conclude that the mathematical model introduced can be used to predict the dynamic stiffness of a porous PEOT/PBT scaffold, and to choose the biomechanically optimal structure for tissue engineering applications.