Blood hematocrit is needed for myocardial ECV. To determine the hematocrit, blood sampling is the standard way, but it is invasive and time-consuming. To avoid the inconvenience of blood sampling, synthetic derivation of hematocrit was suggested in recent studies. In here, we derived the Hct using three prediction methods with multi-features of patient. Investigated methods include the linear regression and AI apporaches. We hypothesized that AI driven multi-feature based synthetic Hct would be more precise than the linear regression. The results of synthetic methods were compared with the laboratory Hct (Lab-Hct) and conventional ECV (Conv-ECV) as the reference.