This article explores the R programming language graphic capacity and appreciates the importance of DHIS2, in provision of data that can be used to make forecast into the future and also decision making today by establishing the existing trends on a number of diseases in Kitui County. Methods applied are simple linear regression to explain the relationship between TB cases detected and TB HIV+ cases. In this study we noticed there is almost a perfect correlation between the two. We also use line graphs and pie charts to graphically display some sickness scenarios.Data used in this article was obtained from DHIS2 platform for the period 2013-2017. The article addresses the most prevalent health problems in Kitui County including Malaria, Skin diseases, Pneumonia, intestinal worms and Diarrhoea. Moreover, assessment is done to explain the general health status since 2013 TO 2017 including analysis of maternal and neonatal deaths. This is important since it reveals how the county government has been performing since the inception of devolution in 2013.Eventually, a conclusion is drawn and recommendations are given based on the conclusion and findings.The project was done under the constraint of time and challenge of missing data.