In this informal talk we discuss several aspects related to
the importance and use of uncertainty in modeling and simulation. Uncertainty has become pervasive in real computations. In this context, the deterministic solution represents just one possible outcome. We briefly discuss the need for uncertainty in simulations and present several computational efficient models for uncertainty representation in reactive flow simulations. Ties between uncertainty quantification and data assimilation - the process of integrating measurements in simulations - will also be addressed.