Bio-fuels will be an important source of energy in the future. Algal biomass is, compared to other sources of inland raised bio-fuel, a very productive way to produce energy. For instance, replacing all the diesel in the U.S. with soy biodiesel would take half of the land mass of the U.S. to grow those soybeans, but if algae fuel replace all the petroleum fuel in the United States it would require an area only a few thousand miles larger than Maryland [w1]. For effective operations and to enable scaling bio-fuel operations, algal bio-fuel needs a health management and a control system to allow growers both have an insight of the current state of health of the bio-fuel mass, and understanding which way the health is trending, as well as control of the bio-fuel mass to avert undesired events (such as a crash). Some attempts of modelling algal biomass behaviour has been already done, but it has been more focus in the growth phase. One of the objectives in this paper is to find a model that can follow all the algal biomass behaviour, including the death phases. This report will focus in the model-based prognosis for, with a model of the algal biomass, try to predict the future behaviour. This information will be useful to change future operating conditions to avoid undesired events and maximizing productivity.