Ventricular suction (VS) is an event caused by operating a rotary ventricular assist device (VAD) at a high speed in a patient with low blood volume in the left ventricle (LV). VS occurs when the blood flow out of the ventricle exceeds the flow into the ventricle, causing the ventricle to collapse. Because of this, it is risky to use a VAD on a long-term basis without changing the speed as the demand of a human body changes dramatically over time. As a result, a controller that can automatically adjust pump speed based on a patient's physiological needs with the capability of suction detection and avoidance would be important for developing a rotary VAD for long-term use. Computer modeling of the cardiovascular system has been used extensively for controller design and testing. To test the capability of a VAD controller to respond to VS, a mathematical model that can simulate VS must be integrated with a cardiovascular system model. In this paper, a nonlinear resistance as a function of the LV pressure, the absolute value of the LV pressure derivative, and the pump inlet pressure was identified to model VS. This was done by fitting a curve to data sets from animal experiments with the HeartMate II VAD. The model fit the data well with an average root-mean-squared (RMS) error of 10.93%. The model was validated against 23 different animal data sets with a mean RMS error of 29.98%. An existing suction model was tested with the same validation data sets and yielded a mean RMS error of 67.41%. The newly developed model showed a significant improvement from the existing model. It will be integrated with a cardiovascular model for future development of a suction detector and physiologic controller for a VAD.