Transportation, restrictive Voter ID laws, and proximity to polling locations are just a few examples of critical barriers to potential voters; however, much of this research examines national and state level trends, limiting its usefulness in generating local policy recommendations. This research sought to determine if there are regional differences in the obstacles that residents in different San Diego city council districts experience in their effort to cast their ballot. In addition, this research also reported on the regional levels of support for proposed initiatives designed to increase access to voting and election resources. To do this, this research used a variety of publicly available data from sources such as the Census, American Community Survey (ACS), San Diego Association of Governments (SANDAG), and the San Diego County Registrar of Voters (ROV). This research also conducted a convenience survey of 489 San Diego residents which asked questions relating to their basic demographic information, voting history, obstacles they may experience in the electoral process, and their support for potential initiatives to increase access to voting and election resources. With this information, logistic regression models, decision trees, and random forests were built to measure the relationship between socio-economic explanatory variables and the likelihood that a respondent will vote. This analysis found that job schedules and long waits at polling places were the most prominent barriers to participation for respondents who wished to vote. This research also found the most widely supported initiative to increase voter turnout were making election day a holiday and expanding early voting. There are also regional differences in the reported obstacles that respondents faced in their efforts to cast their ballots and their support for potential solutions. These differences can be understood, in part, by educational attainment, income, age, and race-ethnicity profiles. The predictive analysis for this research found that based on the survey data, respondents who were determined most likely to vote were also most likely to have higher incomes, higher levels of educational attainment, be older in age, and identify as White or Asian.