Predicting and Analyzing Law-Making in Kenya

Modelling and analyzing parliamentary legislation, roll-call votes and order of proceedings in developed countries has received significant attention in recent years. In this paper, we focused on understanding the bills introduced in a developing democracy, the Kenyan bicameral parliament. We developed and trained machine learning models on a combination of features extracted from the bills to predict the outcome - if a bill will been acted or not. We observed that the texts in a bill are not as relevant as the year and month the bill was introduced and the category the bill belongs to.