For over 40 years archaeologists have been using predictive modelling to locate
archaeological sites. While great strides have been made in the theory and methods of site
predictive modelling there are still unresolved issues like a lack of theory, poor data, biased datasets
and poor accuracy and precision in the models. This thesis attempts to address the problems of poor
model performance and lack of theory driven models through the development of a new method for
predictive modelling, agent based modelling. Applying GIS and agent based modelling tools to a
project area in southeaster New Mexico this new methodology explored possible behaviours that
resulted in site formation such as access to water resources, travel routes and resource exploitation.
The results in regards to improved accuracy over traditional methods were inconclusive as a data
error was found in the previously created predictive models for the area that were to be used as a
comparison. But, the project was more successful in providing explanatory reasons for site
placement based on the models created. This work has the potential to open up predictive
modelling to wider archaeology audiences, such as those based at universities. Additional findings
also impacted other areas of archaeological investigation outside of predictive modelling, such as
least cost path analyses and resource gathering analyses