Climate change mitigation efforts face increasing demand for animal source food consumption and dairy in particular. Therefore, it is necessary to understand the differences in dairy consumption levels and underlying drivers on a global scale. We attempt to estimate drivers of milk consumption by using a panel regression clustering approach and analyzing the relative importance by applying a Shorrocks-Shapley decomposition of the R-squared. Further, we show how the results change when we incorporate income projections for the years 2050 and 2100. Results suggest that, using a panel data set from 2000 to 2020 for 120 countries, socio-economic milk consumption drivers can be allocated to six different clusters with price elasticities ranging from -1.085 to 0.450 and income elasticities from -0.527 and 1.084. Decomposing the R-squared shows that the value of milk industry seems to explain most of the variance of milk consumption. When considering income projections until the mid and end century, we find that the share of young population gains statistical significance. Future research should investigate how fiscal climate change adaptation policies could be designed effectively while considering heterogeneous milk demand drivers.