This study developed a comprehensive framework integrating ecosystem services (ESs), ecological adaptability, and ornamental value to guide tree species selection in historic cities constrained by soil salinization and subsurface heritage conservation. Taking Kaifeng, Henan Province, as a case study, we employed field surveys, i-Tree Eco, the Analytic Hierarchy Process, and K-means clustering to evaluate trees across protective, park, attached, and square green spaces. Results showed that carbon-related services dominated Kaifeng’s urban ES profile, with carbon storage (CS) and sequestration (CSE) value densities of 9.09 ¥·m⁻² and 0.84 ¥·m⁻²·y⁻¹, respectively. Air pollutant removal (AR) (0.21 ¥·m⁻²·y⁻¹) and P (0.009 ¥·m⁻²·y⁻¹) values remained comparatively low. Camphora officinarum Nees ex Wall delivered the highest annual ES value per tree (33.24 ¥·y⁻¹). Plaza greenery outperformed other space types in overall service provision, and deciduous broadleaf species generated greater ES value than evergreen conifers. Cluster analysis identified four functional groups: stress-tolerant pioneers, balanced adapters, high-efficiency carbon sinks, and ornamental specialists—each suited to specific green space contexts. This integrated framework offers a transferable approach for evidence-based tree selection in saline historic cities, supporting nature-based solutions in urban green space (UGS) planning.