Based on the observation data from monitoring stations in the Xinghua river-crab aquaculture area from 1991 to 2024, this paper established a forecasting model between meteorological factors and the first-day stocking of crab seedlings using the stepwise regression method. It provides technical support for river-crab farmers to avoid low-temperature risks and select accurate stocking periods so as to improve the survival rate of crab seedlings. The results showed that from 1991 to 2024, the average first stocking date in Xinghua fell on February 21 (in common years) or February 22 (in leap years), with a trend of advancing over time at a rate of 0.09 days/year. The ten-day mean temperature, precipitation, and sunshine duration prior to the stocking period were significantly correlated with the first stocking date. Using stepwise regression, three key factors were identified, including sunshine duration in late January, extreme minimum temperature in early March, and extreme maximum temperature in mid-September of the previous year, to construct a prediction model for the first stocking date based on preceding meteorological factors. The model demonstrated good fitting performance for the data of 1991-2015; for the year of 2016-2024, the minimum error between predicted and actual values was 0.76 days, with an average prediction error of 3.65 days. The model results are reasonably reliable and can better serve crab farming production.