Abstract: Elderly-friendly communities are a critical component of elderly care service system planning. This study uses national elderly-friendly communities as its research focus, with an emphasis on rural areas. By employing methods such as kernel density estimation, standard deviational ellipse, spatial autocorrelation, geographic detector analysis, and geographically weighted regression, it examines the spatial distribution patterns and influencing factors of rural elderly-friendly communities in China. The findings reveal three key insights: Spatial distribution is concentrated in southeastern China, forming three primary clusters: Chengdu-Chongqing, Yangtze River Delta, and Beijing-Tianjin. The density of these communities gradually decreases from cluster cores to surrounding regions. Rural elderly-friendly communities exhibit significant spatial clustering, with 'High-High' clusters (positive spatial association) concentrated in the Yangtze River Delta and Chengdu-Chongqing regions, and 'Low-Low' clusters (negative spatial association) predominantly in northwest and northeast China. Four categories of factors significantly shape spatial distribution: regional natural geography, economic development level, socio-cultural environment, and transportation accessibility. This research offers actionable recommendations for optimizing the planning and development of rural elderly-friendly communities.