The study’s primary purpose is to assess the probabilistic impact of corruption in climate finance on achieving zero emissions. This scientific problem is highly relevant since the largest recipients of international climate assistance are countries with significant corruption in the public sector. Thus, it is necessary to increase the transparency in the use of international assistance funds and strengthen accountability. The study used the methods of survival analysis, namely the Kaplan-Meier approach and the Cox proportional hazards regression model, to investigate 114 countries that received international climate assistance during 2005-2021. The empirical analysis showed that the most probable time frame for achieving 5% reduction in greenhouse gas emissions is five years. Moreover, the response of climate finance to reducing greenhouse emissions is faster in countries with medium levels of corruption than in countries with high and very high levels of corruption. Two covariates (the level of corruption and the volume of climate finance) likely to affect the achievement of net zero emissions were chosen to build the Cox proportional hazards model. The study empirically confirms that with a 1-point increase in the Corruption Perceptions Index, the probability of reducing emissions increases by 2.4581%, while the volume of climate finance does not have a statistically significant impact on the performance indicator. It suggests that current climate investment in underdeveloped countries is incapable of mitigating the negative impact of climate change.