While the impact of climate on the health of the elderly population has been extensively documented, less attention has been paid to the elderly migrant population. Using data from the 2017 national dynamic monitoring survey of floating populations in China, this study constructs a Probit model to analyze the effects of climate variables (including average temperature, sunshine duration, and precipitation) on the health status of the elderly migrant population, controlling for individual, migration, healthcare, and socio-economic factors. The sample statistical results show that over 80% of the elderly migrant population rate their health as good, but objectively, over 46% of them are at risk of illness, indicating a significant health concern for this group. The baseline results indicate that climate significantly affects the health status of the elderly migrant population, with higher average temperatures increasing their health probability. Instrumental variable analysis confirms the robustness of these results after addressing endogeneity. Heterogeneous results show that the average temperature significantly affects the objective health status of both young and middle-aged and elderly migrant populations. An increase in average temperature and sunshine duration significantly reduces the objective probability of illness among long-term migrant elderly populations, while an increase in precipitation significantly reduces the self-rated health probability of long-term migrant elderly populations. The climate has a more significant impact on the health status of the elderly migrant population in the central and western regions of China.