Long-term time series data are not available for many of the African Great Lakes. This precludes fitting ecosystem model parameters to time series data, and we do not know how reliable non-fitted models are compared to fitted ones in terms of predicting consequences of alternative management strategies. To investigate this, we generate a historical Ecopath with Ecosim (EwE) model for Lake Victoria (East Africa), fitted to time series data (1980–2015), and a present-day EwE model (representing average conditions for the period 2010–2015). We do scenario simulations using the present-day model and the comparable 2015 end-state of the historical model, and test if incorporating information on short-term biomass trends by adjusting biomass accumulation (BA) parameter in the present-day model increases its reliability. We find that there are differences in model predictions, but those differences can be lessened by adjusting BA terms in the present-day model to reflect biomass trends from short-term empirical data. We also compare the models with and without fitted vulnerability parameters. The models generally give comparable results for the dominant commercial fisheries at low fishing pressure; when fishing mortality is increased, the models give variable predictions. This study adds to the current understanding of the limitations of EwE models that are not challenged to reproduce long-term historical fishery responses to perturbations. We conclude that for the less productive groups, as well as groups that suffer heavy mortality (either due to predation or fisheries), it may be appropriate to use negative BA as first draft assumption in present-day models.