One of the main issues in urban sustainability and environmental assessment relates to the selection of indicators (SOCCO, 2000), as there are already many international and recognised core sets (DELSANTE, 2007; LEE; CHAN 2009). Nevertheless, specific local contexts are still in need of appropriate, original indicators and indices (MALCEVSCHI, 2004). This paper deals with the urban quality assessment of medium-density neighbourhoods, which typically include dwellings but also public functions, public spaces and urban infrastructure. The evaluation method is based on a set of 74 indicators used within a specific computational method that is based on scores and defined through pairwise comparison matrices (SOCCO, 2003) to convert qualitative and quantitative evaluations into scores (0 to +100). The assessment involved two different urban contexts in the cities of Lodi and Genoa (Italy). It tests if the set can be used in other sites and cities; the results show significant findings and potentialities, but also some limitations. As significant connections have already been found between urban quality and well-being surveys of inhabitants (ORLANDO, 2007), the possibility to act comparatively in different contexts increases overall research potentiality. The paper deals focus on neighbourhood scale in medium density cities, that usually includes not only dwellings but also public functions, spaces and urban infrastructures. A specific set of 74 indicators is set to effectively describe medium density neighbourhoods. It has been created and tested in European cities, but it can potentially be adapted to other urban contexts. Each indicator has been accurately described through quantitative and/or qualitative data, so that it can be assessed through a range of 4 qualitative evaluations (from excellent to not sufficient).To translate these evaluation in numeric values a specific methodology is used, based on scores and defined through pairwise comparison matrices. Indicators are organised in tree structure, with four main domains and 18 macro-indicators. Each indicator is finally expressed through a numeric value and weighted in relationship with others. The final overall urban quality index translate the 74 indicators into a synthetic numeric value: it can be monitored, compared with other case studies and precedents, interlaced with other data (e.g. pollution, health). Meaningful relationships have already been found with well-being surveys on resident inhabitants, and further development could be linked to e.g. urban quality of life.