Trust is a key factor in the effectiveness of the Wireless Emergency Alerts (WEA) service. Alert originators (AOs) must trust WEA to deliver alerts to the public in an accurate and timely manner. Members of the public must also trust the WEA service before they will act on the alerts that they receive. This research aimed to develop a trust model to enable the Federal Emergency Management Agency (FEMA) to maximize the effectiveness of WEA and provide guidance for AOs that would support them in using WEA in a manner that maximizes public safety. The research method included Bayesian belief networks to model trust in WEA because they enable reasoning about and modeling of uncertainty. The research approach was to build models that could predict the levels of AO trust and public trust in specific scenarios, validate these models using data collected from AOs and the public, and execute simulations on these models for numerous scenarios to identify recommendations to AOs and FEMA for actions to take that increase trust and actions to avoid that decrease trust. This report describes the process used to develop and validate the trust models and the resulting structure and functionality of the models.