For many applications, it would be extremely useful to have insights into river flows at timescales of a few weeks to months ahead. However, seasonal predictions of this type are necessarily probabilistic which raises challenges both in generating forecasts and their interpretation. Despite this, an increasing number of studies have shown promising results and this is an active area for research. In this paper, we discuss insights gained from previous studies using a novel combined water balance and data-driven approach for two of Africa's largest lakes, Lake Victoria and Lake Malawi. Factors which increased predictability included the unusually long hydrological response times and statistically significant links to ocean-atmosphere processes such as the Indian Ocean Dipole. Other lessons learned included the benefits of data assimilation and the need for care in the choice of performance metrics.