Computer Heart modeling serves as a pivotal tool across diverse disciplines, facilitating the interpretation of electrical and mechanical information. The process of generating accurate patient-specific 3D heart model poses significant challenges, demanding time, expertise, and computational resources as established by both manual and artificial intelligent and deep-learning driven methods. In this paper, we introduce a novel morphing algorithm for generating 3D heart models with minimal input. By pinpointing four key anatomical landmarks which are the heart apex and the centers of the Mitral, Pulmonary, and Tricuspid valves - our approach leverages a template model for the ventricles. This algorithm scales the ventricles of the heart along their primary axes and aligns them using translation and rotation based on the landmark locations. It was tested on a dataset of 94 models revealing promising outcomes, both visually and quantitatively. Specifically, the median percentage error in the estimation of endocardial left volume and of endocardial right volume are lower than 13% and 6%, respectively. Importantly, our method offers a rapid, efficient alternative, making it accessible to a broader range of users which would open the way for a new modeling method that is fast and might satisfy the need in inverse ECG applications.