The development and analysis of predictive, mechanistic models of biological phenomena is hampered by uncertainty in the parameters that govern the interactions between components. In this talk, I will discuss new techniques for verifying the properties of models in the presence of parameter uncertainty. Our method combines parameter estimation with statistical model checking to address the following problem: "given model M and data Y, does property φ hold with probability p?" We demonstrate our method on a model of T-cell signaling.