The optimization and control of biochemical processes require the previous establishment of mathematical models that can describe the effect of process variables on their actual kinetics. Environmental temperature is a modulating factor to which the algal cells respond continuously by adjusting their rates of cellular reactions, their nutritional requirements, and, consequently, their biomass composition. Light intensity is an exhaustible resource, indispensable to autotrophic organisms. The effects of light intensity and temperature on growth of the microalga Pavlova lutheri, which have hardly been considered to date in a simultaneous fashion, were experimentally assessed using a factorial experimental design; in this way, the effects of each variable independently and their interactions could be quantified, using maximum biomass (X(max)) or maximum specific growth rate (mu(max)) as objective functions. The preliminary results produced indicated that light intensity plays a more important role on mu(max) than temperature; in the case of X(max), both temperature and, to a lesser extent, light intensity do apparently play a role. The highest values of X(max) were associated with low temperatures and high light intensities; a similar behavior could be observed for mu(max) concerning light intensity, although the dependency on temperature did not seem to be as important. A more complex mechanistic model was then postulated, incorporating light and temperature as input variables, which was successfully fitted to the experimental data generated during batch cultivation of P. lutheri.