Sugar Research Australia has helped the Australian sugarcane industry to manage diseases through the development of disease-resistant varieties. Candidate varieties are screened for resistance to major diseases, before release to the industry, and data collected from screening trials are used to predict the disease rating of each variety. A linear mixed model is fitted to the combined historical and most recent trial and predictions of the average disease ratings for each standard, and candidate varieties are obtained from the model. Using the predicted ratings from current data, both standard and candidate varieties are assigned to one of three resistance groups, i.e. resistant, intermediate, or susceptible. Varieties in each resistance group are presented in a tabular form, but problems have been identified in the two-stage analysis and the tabular report. To rectify the problems, this study aimed to (a) account for trial data variation associated with environmental and biological parameters, (b) replace the resistance groups with a confidence interval, and (c) develop an easily grasped visual illustration that indicates the predicted resistance of a variety plus variation in trial data. The 10-year historical data used in the study consisted of 10 top commercial varieties, nine standard varieties and a combination of six newly released varieties and advanced clones. A Box-Cox transformation was applied to the ratings and then a weighted linear mixed model was fitted to the data. Several combinations of parameters in the model were used, such as trial name or trial year as a random effect and trial confidence as a weight variable. Predicted average ratings and the 95% confidence interval (CI) for the predicted average ratings were calculated from the models. As a visual representation of the predictions from the best model, a scatter plot with the confidence interval (as error bars) was used. The visual reports were presented at the 2019 industry meetings following support by the Regional Variety Committees.