Micro-computed tomography (Micro-CT) images can be used to quantitatively represent bone geometry through a range of computed attenuation-based parameters. Nonetheless, those parameters remain indirect indices of bone microarchitectural strength and require further computational tools to interpret bone structural stiffness and potential for mechanical failure. Finite element analysis (FEA) can be applied to measure trabecular bone stiffness and potentially predict the location of structural failure in preclinical animal models of osteoporosis, although that procedure from image segmentation of Micro-CT derived bone geometry to FEA is often challenging and computationally expensive, resulting in failure of the model to build. Notably, the selection of resolution and threshold for bone segmentation are key steps that greatly affect computational complexity and validity. In the following study, we evaluated an approach whereby Micro-CT derived grayscale attenuation and segmentation data guided the selection of trabecular bone for analysis by FEA. We further correlated those FEA results to both two- and three-dimensional bone microarchitecture from sham and ovariectomized (OVX) rats (n = 10/group). A virtual cylinder of vertebral trabecular bone 40% in length from the caudal side was selected for FEA, because Micro-CT based image analysis indicated the largest differences in microarchitecture between the two groups resided there. Bone stiffness was calculated using FEA and statistically correlated with the three-dimensional values of bone volume/tissue volume, bone mineral density, fractal dimension, trabecular separation, and trabecular bone pattern factor. Our method simplified the process for the assessment of trabecular bone stiffness by FEA from Micro-CT images and highlighted the importance of bone microarchitecture in conferring significantly increased bone quality capable of resisting failure due to increased mechanical loading.