Among many weeds that cause crop loss, parthenium was found to be the most terrible onernaccording to some exploratory studies. The problem of parthenium is not only that it cause veryrnsever crop loss, but also it cause health problems to human and animal beings. Control ofrnParthenium by Farmers ,cultural and labour intensive, caused farmers to suffer from skin allergy,rnitching, fever, and asthma.rnThis study tried to popularize different Generalized linear models for modeling agricultural datarnwhich is used for describing the data sufficiently well and then identify the natural relationshiprnbetween different variables for further analayis as well as applications. Generalized linear modelsrn(GLMs) are used to do regression modeling for non-normal data with a minimum of extrarncomplication compared with normal linear regression. One of the available programs that isrnimportant in current statistical practice is the GLM procedure in the SAS software package.rnThe study is based on the result of a parthenium and other species count data, secondaryrndata,obtained from Ethiopian instisute of Agricultre research. Descriptive statistics supported byrngraphical presentations have been discussed to show the dominance of parthenium on other speciesrnper plot area. Furthermore, to evaluate the probability of a plot or a quadrant to be free ofrnparthenium, models form GLM family are applied to the data using SAS software.rnBased on the parameter estimates, fitted models were formulated, parameters are interpreted andrncomparison of fitted models conducted. In this model fitting process, an attempt was made tornalleviate a confusion of which model to which data. The logit and probit model fitting gives similarrnresults for the same data as expected and the choice of one model cannot be made based on AIC,rnbecause the AIC for both models is the same.rnThe poisson regression model fit is found to be inadequate for two different variables, as itsrnDeviance value is far from one. The Negative Binomial Model gives a better fit and its Deviancernshows the model is adequate for the same data used for poisson regression. The multinomial logitrnmodel for parthenium infestation in five categories as dependent variable and the sum of all otherrnspecies gives a better result, as infestation level increase i.e as the severity of parthenium infestationrnincrease, the number of the sum of other species gets low which in turn means that the probability ofrngetting other species gets very low