Objectives: The study aimed to determine the tobacco smoking patterns in Kenya. Methods: This research project
used the Kenya GATS 2014 data, in which a sample of 5436 total people was interviewed. However since the research
focussed on modelling tobacco smoking pattern in Kenya, data from only 4418 people was used for the analysis. Data from
1018 people in the sample was dropped because information about the individuals smoking pattern, age or work status could
not be found. Data Analysis: The data was analysed using R-software version 3.0.2, and report presented in form of tables and
graphs. Results: This project found out that there is likelihood of a person being a heavy smoker, light smoker or Non-smoker,
if the person works in the Government and Non-government /private organization, self-employed or Unemployed. The overall
effect of work status was statistically significant with a chi-square value of 129.722 (p-value<0.0001). Conclusion: The results
show that a person’s working status and their age are good predictors of a specific smoking pattern. From the results we have
more people smoking as they grow old