The remediation of leachate from (municipal) landfills is becoming an increasing challenge for many government authorities. There is mounting interest in using bioremediation as a means of stripping these contaminants from the leachate and concentrating it within biological material, typically microalgae. Additionally, there is significant interest in the production of lipids from waste streams using microalgae. Landfill leachate typically hosts a suite of inorganic contaminants and therefore it is of great interest to evaluate the ability of different microalgae to (1) survive, (2) grow and (3) accumulate a range of heavy metals under field conditions. While this provides realism, it does however, require a firm understanding of how the interacting biology and chemistry of the microalgae and leachate constituents interact including the potential for feedback loops, delays and nonlinear functional relationships. To this end, we propose the use of a system dynamics modelling framework to develop a 'stock' (reservoirs) and 'flow' system dynamics model that explores the algae growth dynamics and the heavy metal adsorption kinetics simultaneously. We have developed a model that mimics the temporal evolution of metal removal from a leachate into a biological mixture comprising of four common marine microalgae species- Nanochloropsis, Pavlova lutheri, Tetraselmis chuii and Chaetoceros muelleri. The growth dynamics of the microalgae species is modelled using four separate stocks that represent the concentration of each of the four species with inputs and outputs consisting of growth and mortality respectively. Growth is light-limited while both growth and mortality are assumed to be temperature dependent. Similarly, the five metals monitored in the leachate (iron, manganese, barium, cerium and lanthanum) are each represented by a stock. The uptake kinetics of the metals (removal from the leachate) are modelled using adsorption kinetics, taking into account that there are a finite amount of adsorption sites on the microalgae. The model is primarily parameterised from data obtained through pilot studies using the four marine microalgal species. Two photobioreactors employing light regimes, mixing and aeration were dosed with landfill leachate and simultaneously seeded with the four microalgal species and left for three days. The leachate and the microalgae species were analysed for metal content at the beginning and end of the batch experiment. The use of two reactors and subsequent two sets of results allowing the microalgae growth kinetics (growth and mortality) to be simultaneously fitted to the data. It is assumed that any potential effects of leachate toxicity on microalgae growth dynamics will be implicitly included in the respective growth and mortality rate constants. Overall, this system dynamics model provides a mechanism for understanding and predicting the bioremediating ability of different algae under realistic conditions.