A bio-economic model is developed that allows a detailed representation of optimal weed control decisions. It implements an output damage control approach for German silage maize production, considering almost eighty mechanical and herbicide based weed control options against over thirty weeds, working with detailed data on weed abundance and yields for more than three hundred municipalities in the federal state of North-Rhine-Westphalia. We apply the model to simulate economic optimal weed control over two growing periods under current environmental standards and under the scenario of a glyphosate ban as recently discussed after glyphosate was classified as probably carcinogenic to humans. Considering different levels of weed pressure, we find that adjustments in the intensity of mechanical pre-sowing strategies are an optimal response to a glyphosate ban, causing yield reductions of about 1%. In contrast, we find little evidence for a substitution towards selective herbicides post-sowing. On average, the aggregated economic impacts of a glyphosate ban are small, i.e. at about € 1–2/ha, but single farms may face higher losses at about € 10/ha.