The “Sustainable neighborhoods” has become widely proposed objective of urban planners, scholars, and local government agencies. However, after decades of discussion, there is still no consensus on the definition of sustainable neighborhoods (Sawicki and Flynn, 1996; Dluhy and Swartz 2006; Song and Knaap,2007; Galster 2010). To gain new information on this issue, this paper develops a quantitative method for classifying neighborhood types. It starts by measuring a set of more than 100 neighborhood sustainable indicators. The initial set of indicators includes education, housing, neighborhood quality and social capital, neighborhood environment and health, employment and transportation. Data are gathered from various sources, including the National Center for Smart Growth (NCSG) data inventory, U.S. Census, Bureau of Economic Analysis (BEA), Environmental Protection Agency (EPA), many government agencies and private vendors. GIS mapping is used to visualize and identify variations in neighborhood attributes at the most detailed level (e.g census tracts). Factor analysis is then used to reduce the number of indicators to a small set of dimensions that capture essential differences in neighborhood types in terms of social, economic, and environmental dimensions. These factors loadings are used as inputs to a cluster analysis to identify unique neighborhood types. Finally, different types of neighborhoods are visualized using a GIS tool for further evaluation. The proposed quantitative analysis will help illustrate variations in neighborhood types and their spatial patterns in the Baltimore metropolitan region. This framework offers new insights on what is a sustainable neighborhood.