Heart failure with preserved ejection fraction (HFpEF) affects approximately one-half of the heart failure patient population, and its prevalence is suspected to grow significantly over the next decade. This condition is associated with high morbidity and mortality, due to the lack of effective therapeutic options. HFpEF is characterized by left ventricular (LV) stiffening, which hinders heart function, resulting in limited LV expansion. These changes may engender LV pressure elevation, remodeling, and, eventually, heart failure. However, the exact biomechanical process and its causes remain unclear. So far, HFpEF has been investigated from biological and computational perspectives. Physical quantification of the myocardial parameters following tissue stiffening has shown high variability and a lack of standardization. Very few in-silico models were developed to evaluate specific solutions for HFpEF, despite the ongoing interest in medical devices as possible treatments for a vast range of diseases and conditions. This study fills in these gaps by introducing a comprehensive framework that uses the Living heart porcine model (Simulia, Dassault Systèmes, Providence, RI, USA) to generate computational model pairs of the same subject that include a healthy configuration as a reference before the induction of HFpEF, and a corresponding post-induction diseased configuration. The HFpEF models were then used for the implantation of an LV expander device to examine its effectiveness and in order to perform basic optimization. The methodologies applied in this study have led to new insights into tissue stiffening and therapeutic possibilities in HFpEF. The proposed framework can serve as the backbone for a larger-scale analysis of many HFpEF phenotypes for evaluation, accurate classification, and treatment tailoring as well as investigating and modeling other heart conditions.