Urban RBD (Recreational Business District), a place where local residents and tourists go for leisure, tourism and consumption, is widely accepted as an indispensable component of urban recreation system in recent years. However, existing research in urban RBD puts an emphasis on its conceptual aspects (i.e., classification, influence, spatial structure), and empirical and quantitative studies have been largely ignored. Firstly, a summary about urban RBDs’ characteristics from the perspectives of location, scale, users, function, and culture was made. Based on previous literature and RBDs’ characteristics and attributes, this study divides urban RBD into three groups, namely: Large Shopping Center (LSC), Commercial Pedestrian Street (CPS), and Urban Leisure Area (ULA). Quantitative methods, such as Gini Coefficient, Spatial Interpolation, Kernel Density Estimation, and Geographical Detector, were employed to collect and analyse data of three types of urban RBDs in Beijing in 1990, 2000, and 2014, respectively, and the spatial-temporal evolution pattern as well as distribution characteristics of urban RBDs were analyzed with the aid of ArcGIS software. The results show: (1) The total number and scale of urban RBDs in Beijing have been expanding, with urban RBDs increasing by 8.20% and 7.26% per year in 1990-2000, and 2000-2014, respectively; (2) spatial agglomeration of urban RBD in Beijing keeps strengthening, and the trend that all types of urban RBDs in Beijing are spatially agglomerated is continuing; However, there exist some variances in terms of their growth speed and degree; (3) the spatial structure evolution model of urban RBDs in Beijing is as one core concentration—two cores development—multi-core diffusion; (4) According to the statistics from database concerning traffic, resident and tourist density, tourism attractions and land price in Beijing, the results showed that urban RBDs were generally located in areas with low traffic density, tourist attractions, high resident and tourist population density, and relatively high land valuations; (5) tourists density strongly influenced the scale of each urban RBD type, compared with other factors.