With the rise of femicide and reportings of domestic violence in Kenya, the overall safety and well-being of women continues to emanate concern. In this study, connections between Kenya's socioeconomic climate and women's progress are examined through Multivariate Regression Analysis. Other techniques included in this study are Time Series, Multiple Regression, and the Genetic Algorithm for model selection. These methods are applied to explore the relationships between 9 women empowerment indicators and 37 measurements of different aspects of Kenyan society. Time will also be considered to account for the time series component, resulting in 38 total predictors. To reduce multi-collinearity within the predictors of the data set, 5 different models through a subset of the predictors in categories of economics, politics, health, education, and technology.