Improving soybean production in Europe under climate change needs a good prediction of cultivar phenology under different temperature and photoperiod conditions. For that purpose, a simple phenology algorithm (SPA) was developed (Schoving et al., 2020). Before being applied, SPA requires the calibration of 7 genotypic parameters; therefore, a simple phenotyping method was designed and set up under natural and controlled conditions to determine these parameters. Two experiments were performed with 10 cultivars in 2017 and 5 cultivars in 2022 (from MG 000 to II): 1- A pot experiment on the Heliaphen platform (INRAE Toulouse, SW France) under natural climatic conditions with 4 to 6 planting dates (from March to September). The main phenological stages were recorded (BBCH and Fehr & Caviness scales), once or twice a week. 2- An experiment on germination response to temperature (from 4 to 43°C) under controlled conditions (cold room and incubator). Mean cardinal temperatures (minimum, optimum, and maximum) for germination were ca. 2, 30, and 40°C, respectively with significant differences among cultivars. For most stages, ANOVA analysis showed a highly significant effect of the interaction between cultivar and planting date on thermal time accumulation. A photothermal time formalism was used to evaluate by optimization the sensitivity of each cultivar to photoperiod and the optimal Physiological Development Days of the cultivar to complete a given phenological phase (PDD). The optimization of the PDD plant parameter from hourly temperature values instead of daily values improved the prediction of phenology by SPA. This approach - simple cultivar phenotyping and photothermal algorithm - is currently evaluated on several grain legumes to design more diversified and agroecological cropping systems.