The sheep rumen submodel MollyRum14 was evaluated on its methane and VFA predictions against data from respiration-chamber trials conducted with sheep fed perennial ryegrass, white clover, chicory, forage rape, turnip (leafy and bulb varieties), swedes, kale, or forage radish. We assessed the model's response to substrate degradation rate (settings that affect the rate of cellulose and hemicellulose digestion) and to fermentation stoichiometry (settings that alter nonglucogenic to glucogenic short-chain fatty acid ratios). Model predictions were evaluated against data for methane production (pCH4: g/d), methane yield (yCH4: g/kg DMI), and acetate to propionate ratio (A:P). The predictive ability of the model for both pCH4 and yCH4 was superior for perennial ryegrass than for other forages. Except for swedes and chicory, predictions for yCH4 were correctly ranked across the forages evaluated. Except for forage rape, robust predictions were obtained for all forages using fast degradation kinetics and a predominantly acetogenic stoichiometry. Model predictions for forage rape were enhanced using slow degradation kinetics and a predominantly propionic stoichiometry. These results indicate that MollyRum14 is suitable to predict methane emissions from sheep fed a variety of fresh forages including annual fodder crops. However, a clear understanding of degradation rates and stoichiometries is needed to enhance the utility of the model as a predictive tool. This would allow continuous adjustment of digestion rates and stoichiometries to be potentially tailored to individual forage species.