Index insurance, considered as a powerful tool for stabilizing farmers’ incomes and reducing poverty at its introducing in developing countries, soon disenchanted its promoters. The evolution of demand for this insurance is particularly disappointing in most of the countries that have implemented it. In Burkina Faso, there has been a sharp decline in adhesion and hence in amounts insured. The main reason given by the producers is the lack of payment or the very low level of insurance payout in case of loss of production (basic risk). This study proposes the use of fuzzy classification techniques that allow partial membership of classes to be eligible for a payment to reduce the basic risk and increase the attractiveness of index insurance among cotton producers in Burkina Faso. We have shown that the application of the fuzzy classification technique significantly increases the probability of being compensated (more than three times compared to its current level) but also the premium of the insurance. However, according to Elabed and Carter (2014a), producers would be willing to pay substantial sums to mitigate or completely eliminate the basic risk.