Aims: Atrial stretching and subsequent dilatation are early markers of hypertensive heart disease, which are associated with structural and electrical remodeling that increases the risk of arrhythmias. This work investigates the influence of acute stretch and chronic dilatation arising from hypertensive myocardial overload on the development of atrial fibrillation (AF) episodes in left atrial tissue. For this purpose, coupled modeling of atrial electrical activity with either cardiac wall elastic or growth and remodeling (G&R) processes was carried out. Methods: Eight two-dimensional atrial-tissue models were created to simulate acute stretch and chronic dilatation states by combining an atrial myocyte electrical model with associated hyperelastic or G&R models in a finite element solver for combined modeling. Two control-models, with electrical properties characteristic of persistent atrial fibrillation (peAF) or without electrical remodeling, were differentiated. Acute stretching was studied on four tissue models whose hyperelastic and electrical behaviors were predicted, including the activation of stretch-activated channels (SACs) in two. Chronic dilatation was considered on two tissue models without electrical remodeling, on which the G&R process and its electrical response at advanced phases of dilatation were predicted. The vulnerable window (VW) and the frequency of cardiac arrhythmia generation were computed for each model. Results: The acute stretch study in tissue with peAF and SACs showed greater vulnerability to the development of AF, compared to tissue without electrical remodeling or SACs, with a 38.1% longer VW duration and a mean number of reentries generated 8 times greater. The study of chronic dilatation revealed an increasing vulnerability to the development of AF compared to the control, with an increase in VW of 18.9% in a severe phase and an even greater 22.7% in an end-stage phase. Conclusions: Atrial dilatation favors the probability of developing AF. Electrophysiological and G&R modeling and simulation are significant for its predictive study.