Information about soil nutrient carryover dynamics can assist cotton producers with the optimal management of potassium (K) fertilizer. Optimal K management promotes cotton plant health, may decrease input costs, and increases cotton lint yields. A dynamic programming model was developed to determine optimal K application rates and economic returns under different soil information scenarios based on cotton yield response to K fertilizer and fertilizer carryover estimates from a multi-year field trial. A Monte Carlo analysis was conducted to simulate the impact of stochastic input and lint prices and cotton yield on K management over a five-period planning horizon. Results suggest that soil test data could provide important information about K carryover potential, which may lead to more efficient fertilizer use and higher profit margins for cotton producers.