Over the last few decades the interest in Smart Materials - materials which respond to some external stimuli with manifestation of a change in mechanical parameters - has grown tremendously and various engineering applications have been demonstrated using the "smart" function. With the traditional base of the sensor technologies in vogue, the sensing function in a smart system has received considerable attention and is relatively well developed. However, the "actuation" function has posed major challenges. Materials such as piezos, Shape-memory alloys, MR and ER fluids, magnetostrictive materials and some electro-active polymers have all been in focus of the engineering community for building Smart Actuators. Several prototypes have been built to demonstrate the actuator applications. However, converting these ideas into products has remained a major challenge. Issues of reliability of the functional performance, degradation with time, response to off-design conditions, hysterisis and nonlinear responses, scaling from small-scale and accelerated experiments and the cost of testing several parameters are some of the concerns that have surfaced in translating prototypes to products. With the advances in computational capabilities and materials science, building math-models for the behavior of these materials and the actuators built out of them is being seen as a fruitful direction in achieving predictive capability so much needed to help sort out many of the issues mentioned above. General Motors R&D has taken a significant step in this direction with a consorted effort to create math models of smart materials and actuators. Several applications in the automobile sector are on the anvil. Initial focus of the work is on materials like SMAs, MR Fluids and electro-active polymers. This paper discusses some of the issues in building smart actuators and the work being pursued in creating math-models to help resolve them. The challenges posed by the complex behavior of such materials in creating the models arc highlighted and illustrated with a case study of SMA based devices.