This article addresses the challenge of climate change in agriculture, focusing on the optimization of lettuce production through bio-inspired algorithms supported by an Internet of Things (IoT) architecture. The study underscores the sensitivity of lettuce to thermal stress and proposes a decision-making system that recommends optimal temperature ranges to maximize yield. It highlights the need to maintain optimal environmental temperatures for efficient growth. This research reveals a marked negative correlation between lettuce yield and variables such as evapotranspiration and soil temperature, through data analysis from two regions in Colombia. As a solution, the use of bio-inspired algorithms is proposed to create agricultural recommendation systems capable of identifying temperature ranges that maximize yield. The methodology employs Internet of Things technologies for data collection, and the proposed models include statistical techniques and bio-inspired algorithms, experimentally tested to refine crop management strategies in the face of adverse climatic conditions. The study emphasizes the urgency of implementing adaptive strategies to sustain agricultural productivity and ensure food security in the face of climate volatility.