A two-factor field gradient experiment was conducted to solve the problems of traditional models being difficult to analyze the nonlinear effects of interaction between row spacing and sowing rate. The biological traits and yield components at the stages of key growth in winter rye were systematically measured. The patterns of interaction between population dynamics and yield components during these stages were analyzed to construct a recursive gradient fusion-based random forest model for predicting the yield of winter rye. The results of field experiment showed that the combination of a row spacing of 40 cm and a sowing rate of 535-680 g/40 m² can optimize the light transmittance of canopy， balance the “source sink” relationship， and improve the resistance to stress， achieving coordinated regulation of high and stable yield of winter rye. Samples of plant were systematically collected from different treatment groups at the stage of full maturity in winter rye. A standardized experimental procedure was used to quantitatively characterize key agronomic traits including spike length， spike mass， number of spike nodes， plant height， root length， effective tiller count， leaf count， and seeds per plant. 540 sets of valid data were obtained. A multidimensional feature set encompassing sowing row spacing， seeding rate， spike length， spike mass， number of spike nodes， plant height， root length， effective tiller count， leaf count， and six derived features was constructed using seeds per plant as the prediction target. A hybrid random forest-recursive feature elimination （RF-RFE） with excellent predictive performance （R2=0.951， RMSE=2.28） and generalization ability （OOB-RMSE=4.33） was constructed. The model for predicting yield was used to invert and obtain a three-dimensional response surface for row spacing and seeding rate to identify the high-yield parameters as row spacing ranging from 35 to 49 cm and seeding rate between 535 and 680 g/40 m². The results of marginal effect showed that a 1 cm increase in row spacing beyond 45 cm led to a yield decrease of 1.23 kg， and the marginal benefit decreased as the seeding rate exceeded 650 g/40 m². Therefore， it is recommended to control the row spacing within 40-45 cm and the seeding rate between 600-650 g/40 m² in the practice of production， which can ensure high yield and leave room for the tolerance of operational error.