Climate change continues to risk maize production in Kenya, yet most of the current modeling approaches evaluate climate variables independently and greatly disregard their interaction with soil fertility. This study addresses this gap by creating a deterministic model that clearly incorporates atmospheric \(\textrm{CO}_2\) concentration, temperature, precipitation, soil fertility (nitrogen), and maize yield into a single time-dependent system. Mathematical analysis is performed to establish the existence of the system’s equilibrium points, providing the necessary conditions for their local and global stability. The analytical results of this study are examined using numerical simulations with MATLAB R2024a using data obtained from the literature and online agricultural and climate databases. Numerical simulations reveal that high levels of \(\textrm{CO}_2\) concentration are associated with increased temperature and precipitation, which accelerate soil nutrient exhaustion and contribute to a yield reduction of approximately 10% under high \(\textrm{CO}_2\) sensitivity. The sensitivity analysis of the major parameters \(( \beta _c, \beta _a,\, \text{and}\, \beta _r)\) further proves that temperature and precipitation responses can increase maize yield by 5–10%, whereas soil fertility serves as one of the primary resilience factors that cushion the negative impacts of climate. These findings show that models excluding soil–climate feedbacks may underestimate long-term productivity risks. The policy implications of the findings are that integrated soil fertility management, climate-resistant varieties of maize, and adaptive water management should be prioritized as major elements of contributing to climate-smart agriculture initiatives that can improve maize productivity and food security in Kenya.
