Severe convective storms (SCS) associated with large hail frequently cause considerable damage to vulnerable structures such as buildings, vehicles, photovoltaic installations, and agriculture. In Germany, about one-third of all damage from natural hazards is caused by hail. The goal of HailDetect is to improve existing methods of hail detection including the estimation of hailstone sizes in radar observations of convective objects and thus to lay ground for more reliable warnings that have a high potential for damage prevention through appropriate short-term measures. We will develop and test our methods using the dual-pol reflectivity data from the radar at KIT/IMKTRO. In our approach, we will combine (i) different radar products (radar reflectivity, differential reflectivity and phase, correlation coefficient) with (ii) specific properties of the convective cells and (iii) meteorological fields from the numerical weather prediction, which have been found to be highly relevant for the probability and intensity of SCS in other studies. The central element and major extension compared to previous used methods for hail detection methods is an object-oriented approach of convective events instead of only grid-based analyses..