Campylobacteriosis is a complicated illness that exhibits seasonality and has multiple transmission routes. Some have suggested that vector-borne disease transmission is an important component of the biology with house flies (Musca domestica) acting as mechanical vectors that move the pathogen between contaminated environments and human food. The objectives of this study were to 1) determine if a basic SIR compartment model that included flies as a mechanical vector and also incorporated a seasonally forced environment compartment could be used to capture the observed disease dynamics in Ontario, Canada and 2) use this model to explore changes to campylobacteriosis incidence using projected changes to fly population dynamics and amount of fly activity under different climate change scenarios. Using a framework that incorporated aspects of both compartmental models that include an environmental reservoir, and Ross MacDonald models for vector-borne diseases, we expanded a basic SIR compartmental model to include both a seasonally fluctuating environmental pathogen reservoir and seasonally fluctuating fly population dynamics. This model was fit to campylobacteriosis incidence data from Ontario, Canada. Our model adequately captured the observed incidence of campylobacteriosis in Ontario. Using predicted changes to fly populations under different climate scenarios in combination with a 25% increase to fly activity, our model predicted a 28.15% increase in incidence by 2050 using the medium-low emissions scenario and 30.20% increase using the high emissions scenario. Our model was more sensitive to changes in fly activity versus fly population. This model demonstrates that the dynamics of Campylobacter transmission can be captured by a model that assumes that the primary transmission of the pathogen occurs via insect vectors. This mechanism of disease transmission warrants further research, especially because changes to Canadian temperature profiles under a climate warming scenario will have direct impact on fly population dynamics. In the future, this model could be used to test interventions and prevention strategies, for example, reducing fly populations or fly contact with human food.