DescriptionMany non-oxide ceramics are produced through the densification of a non-oxide powder compact by sintering. A pervasive problem when processing non-oxide powders is the growth of a native oxide layer on the powder surface due to oxidation. Non-oxide powders sinter poorly without the addition of sintering additives to aid in the removal of surface oxide and lower grain boundary energies. Reducing agents, such as C, remove the oxide layer at hold temperatures much below the sintering temperature, forming a significant amount of gas (mainly CO(g)) to be removed. However, sintering additives to enhance densification at the sintering temperature can also form gas at the lower temperature, depleting the additive before reaching the sintering temperature. In this work, we have developed an analytical modeling framework to simulate gas transport and reaction in a porous medium comprised of an arbitrary collection of chemical species. This modeling framework automatically generates the necessary conditions to calculate the thermodynamic equilibrium composition at a given temperature and uses the Dusty Gas Model (DGM) to predict the gas transport. This model accounts for processing parameters including the initial powder composition, sample thickness, porosity, pore radius, and tortuosity of the powder compact, plus the furnace pressure and heating cycle. This model was used to predict the time for complete oxide removal (t_c) and residual composition for three material systems. The C/SiC/SiO2 and B4C/B2O3/C systems were studied to identify the functional dependence of t_c with respect to each processing parameter. Additionally, the C/SiC/SiO2 system was studied to determine optimal heating cycles to control the rate of CO(g) effusion into the furnace while reduce heating times. The C/SiC/SiO2/B4C system was studied to quantify the amount B4C depleted and redistributed during SiO2 removal for samples of varying thicknesses, initial SiO2 content, and holding temperature. B4C was depleted from the center of the samples and re-deposited at the edges; the most drastic compositional variations occurred at higher temperatures and greater SiO2 content. This modeling framework can be applied to other material systems to optimize heating cycles, control gas removal rates and residual sintering additive distributions, and predict t_c due to process variations.