This paper presents a set of experimental indices of multidimensional poverty, using cross-sectional EU-SILC data (European Union Statistics on Income and Living Conditions). EU-SILC is a natural source of data for this measurement work, given its provenance, frequency and comparability. The indices use the Alkire Foster (AF) methodology – a flexible methodology which can accommodate different indicators, weights and cut-offs. The AF methodology underlies the global Multidimensional Poverty Index (MPI) which is released by UNDP’s Human Development Reports and covers over 100 countries, as well as official national measures of multidimensional poverty. In constructing the indices we review the joint distribution within and among potential indicators of multidimensional poverty such as work, income, material deprivation, health, education, and social factors. We also draw on existing comparable indicators that have been constructed with the EU-SILC data, as well as on similar recent multidimensional poverty measures. The time series data enables an analysis of multidimensional poverty dynamics, including analysis of which changes in overall poverty and in indicators are statistically significant across time. The paper also presents sensitivity and robustness tests for the cut-offs and weights, as well as comparisons with other unidimensional and multidimensional indicators currently in use.