Engineering medical applications are enriched by the fabrication potential of the growing technology of Micro-Electro-Mechanical Systems (MEMS). Within this technological expansion, device manufacturing costs, failure and long-term performance reliability are critical issues that have to be resolved using basic probabilistic design methodologies which are yet largely unexploited by industrial and service companies at the mature innovation level. Modeling and testing of high-performance MEMS is a promising route, based upon these methodologies, to enhancing reliability and preventing surface failure. In this paper, we focus on the modeling of the mechanical properties of MEMS, as exemplified by a capacitive accelerometer, using probabilistic techniques. The accuracy of these techniques is also evaluated for the accelerometer with regard to those parameters that affect mainly reliability and failure. The simulated analysis of the mechanical properties is performed with easy-to-use probabilistic software known as “NESSUS”. It is concluded that probabilistic design methodologies are very effective and balanced for making design decisions that can, with both reliability and ease, ensure component or system efficiency.