The maize leafhopper, Dalbulus maidis (DeLong) (Hemiptera: Cicadellidae), is a specialist herbivore that develops on maize plants (Zea mays L., Poaceae). Every year, it is responsible for considerable reductions in yields of the maize fields of the Americas, because alongside its direct damages it is also a vector of three relevant plant pathogens. The transmitted diseases come to have a high incidence, resulting in significant yield losses, thereby forcing farmers and technicians to attempt a tight control of the fields mostly using non-specific insecticides. Decision support systems based on mathematical models may be valuable in helping to reduce the use of agrochemicals in this regard, as they can provide a projection of the future situation based on past and present data. With this precondition, this work aims to apply and validate a physiologically based model to describe populations of D. maidis developing in two experimental fields located in Argentina, which are characterised by different climatic conditions. Experimentation in the two fields involved a 3-year survey during the growing seasons 2009, 2010, and 2011, where the adult populations of maize leafhoppers were monitored from the sowing of maize plants to the end of the phenological stage at which they are most susceptible to D. maidis activity. Results showed a good response of the model in describing maize leafhopper populations, also allowing the possibility of setting a threshold for intervention and a projection of the situation if any control action is applied.