A new method for mapping diseases has been developed using Negative Binomial M-quantile regression models. This approach helps account for errors in the data and reduces the impact of extreme values. The model was tested using Lip cancer data from Scotland and simulations, showing that it provides more accurate estimates with less smoothing compared to other methods. Additionally, the model can be expanded to consider spatial correlations between different areas using Geographically Weighted Regression.