Non-intrusive quadrature-based uncertainty quantification with reconstruction of the distribution of the system response is introduced and applied to the simulation of dense.fluidized beds. This approach relies on the conditional quadrature method of moments (CQMOM) to generate a set of samples of the distribution of multiple uncertain parameters of the model. The moments of thesystem response are directly estimated using Gaussian quadrature formulae, and are used to reconstruct an approximate distribution of the response using extended quadrature method of moments (EQMOM). The approach is demonstrated by considering a bubbling fluidized bed with two uncertain parameters. Contour plots of the mean and standard deviation of volume fraction, phase velocity and pressure are provided. The probability distribution functions of the response are reconstructed using EQMOM with appropriate kernel density functions. The simulation results are compared to experimental data provided by the 2013 NETL small-scale challenge problem. (C) 2014 Elsevier B.V. All rights reserved.