Rapeseed (Brassica napus L.) is an important oilseed crop grown worldwide with a planting area of 6.57 million ha in China, which accounts for about 20% of the world’s total rapeseed planting area. However, in recent years, the planting area in China has decreased by approximately 12.2% due to the low yield and economic benefits. Thus, to ensure oil security, it is necessary to develop high-efficiency cultivation for rapeseed production. Crop growth models are powerful tools to analyze and optimize the yield composition of crops under certain environmental and management conditions. In this study, the CROPGRO-Canola model was first calibrated and evaluated using the rapeseed planting data of four growing seasons in Wuhan with nine nitrogen fertilizer levels (from 120 to 360 kg ha⁻¹) and five planting densities (from 15 to 75 plants m⁻²). The results indicated that the CROPGRO-Canola model simulated rapeseed growth well under different nitrogen rates and planting densities in China, with a simulation error of 0–3 days for the anthesis and maturity dates and a normalized root mean square error lower than 7.48% for the yield. Furthermore, we optimized the management of rapeseed by calculating the marginal net return under 10 nitrogen rates (from 0 to 360 kg ha⁻¹ at an increasing rate of 40 kg ha⁻¹) and 6 planting densities (from 15 to 90 plant m⁻² at an increasing rate of 15 plant m⁻²) from 1989 to 2019. The results indicated that the long-term optimal nitrogen rate was 120–160 kg N ha⁻¹, and the optimal planting density was 45–75 plants m⁻² under normal fertilizer prices. The optimal nitrogen rate decreased with increasing fertilizer price within a reasonable range. In conclusion, long-term rapeseed management can be optimized based on rapeseed and nitrogen cost using long-term weather records and local soil information.