Flash floods represent a major threat to agricultural production in Bangladesh's haor ecosystems, making timely harvesting essential for reducing crop losses and strengthening climate resilience. This study examines how livelihood heterogeneity influences combine harvester adoption and mechanization pathways under flood risk. Using survey data from 360 farm households across the haor districts of Sunamganj, Kishoreganj, and Netrakona, principal component analysis was employed to construct multidimensional livelihood and adaptation indicators, which were subsequently used in cluster analysis to identify livelihood typologies. Binary logit and multinomial logit models were then estimated to assess the relationship between livelihood heterogeneity and combine harvester adoption pathways. The analysis identified four distinct livelihood typologies, namely diversified asset holders, knowledge‐driven adaptive smallholders, networked flood‐resilient adopters, and resource‐constrained flood‐vulnerable traditionalists. Binary logit estimates confirmed significant livelihood heterogeneity in adoption, with predicted probabilities of 0.935, 0.931, 0.760, and 0.133 across the four livelihood typologies, respectively. The multinomial logit analysis further revealed that education level, extension contact, farmer‐group participation, cultivation intensity, and proactive flood‐adaptation practices significantly increased the likelihood of belonging to high‐adoption livelihood pathways, whereas resource constraints and weak institutional engagement were associated with low‐adoption pathways. This study advances the mechanization and climate adaptation literature by explicitly linking livelihood heterogeneity to combine harvester adoption under flood risk. The findings demonstrate that combine harvester adoption is embedded within broader livelihood configurations and functions not only as a labor‐saving technology but also as a climate‐risk management strategy. The findings highlight the need for livelihood‐specific policies that strengthen institutional support, improve access to mechanization services, and enhance the adaptive capacity of vulnerable farmers in flood‐prone environments.