Damaged cardiac muscle tissue caused by ischemia leads to compromised cardiac function. While conventional imaging can view the ischemic tissue, currently there is no clinical way to quantitatively predict improved heart function after revascularization treatment. This increases the decision difficulty of treatment planning as there is no guarantee the heart function will improve enough to justify the cost of revascularization treatment. The complement of biomechanical modelling with conventional imaging offers an alternative method to determine the amount of ischemic tissue which can then be used as a potential predictor to estimate the range of functional improvement. A novel shape optimization technique is presented to predict the contractility of ischemic tissue in an in-silico left ventricle model that has suffered acute myocardial infarction. Preliminary results show that the proposed technique can reconstruct the damage caused by ischemic tissue within 18%. A range of minimum to maximum predicted cardiac improvement can then be given based on this error to help decide if the cost of revascularization treatment is justified.