Decision-making processes must indicate if, how, and when weed control should be practiced. So far, Decision Support Systems (DSSs) for weed control to prevent crop yield losses can guide decisions on “if” and “how.” Experience shows that farmers need a DSS that can also guide when to treat, but this can only be done if the actual weed density observed in the field is known during the crop cycle. Emergence models allow the prediction of daily density, but precision depends on the survey date. This study focuses on the estimation of the date of the survey for the best prediction of the daily density throughout the crop cycle. The predicted daily density of each species can be used by DSSs without any further survey, saving time and money and improving the use of the DSSs. Results showed that the best date is when the actual density of each weed reaches or exceeds 50% emergence, and this is earlier than the critical point date, supporting the validity of the date estimation method. The possibility to provide specific advice for farmers considering a proper mortality rate of weed seedlings is then discussed. The ability to optimize the date of sampling can improve the reliability of decision-making tools for integrated weed management, in agreement with the European Union goal of sustainable use of pesticides and more environmentally sustainable cropping systems through the use of integrated pest management.