Photoperiod and temperature are regarded as two key meteorological factors affecting flowering of woody plants. In this study, we constructed six spring phenological mechanism models driven by photoperiod or temperature (TT model, PP model, TP_a model, TP_b model, TP_c model, and TP_d model) derived from the observations of the first flowering date of Robinia pseudoacacia L. at 57 phenological observation stations in the North China Plain from 1963 to 2018. Based on these data, we firstly calibrated the parameters of each model by the means of simulated annealing algorithm and then selected the optimal one on the basis of indicators. Our purpose is to identify the dominant drivers of the first flowering date of Robinia pseudoacacia L. and try to explain the potential mechanisms of photoperiod and temperature. According to the internal validation indicators, TP_a model was considered to be optimal among the six phenological models with the lowest Akaike Information Criterion (AIC) 2372.3; the correlation coefficient (r) between the simulated and observed Day of Year was 0.86, the Root Mean Squared Error (RMSE) was 4.81 days, and the Nash-Sutcliffe Efficiency (NSE) reached 0.74. The internal validation results indicated that the first flowering date of Robinia pseudoacacia L. was influenced by both photoperiod and temperature. Besides, TP_a model generally outperformed the mean value model at 14 representative phenological observation stations in the North China Plain. In addition, based on the parameterization results of TP_a model, we set 6.5℃ as the base temperature and 4.5h as the base daylength to separately calculate the actual effective accumulated temperature and daylength of the first flowering date of Robinia pseudoacacia L. in the past 56 years. The results showed that there was a significant increasing trend of the actual effective accumulated temperature, with an average increase rate of 4.5℃ · d per decade (P ＜ 0.05), while the actual effective accumulated daylength showed an extremely significant decreasing trend, with an average decrease rate of 23.9h · d per decade (P ＜ 0.01). It indicates that the heat demand of flowering will be completed more rapidly in the context of climate warming, causing an earlier date of the first flowering of Robinia pseudoacacia L., but the intra-annual variation of the photoperiod is only related to the geographical location, and the cumulative demand for daylength takes longer time to complete, so it will suppress the advance rate of the first flowering caused by spring warming to some extent.