Weather constitutes the major source for production risk in agriculture. Weather index can be used construct crop insurance that demand less information and can avoid moral hazard and adverse selection problems. Based on mean-variance model, theoretical results on the optimal insurance coverage and its impact from risk preference, basis risk, and premium loading are derived, which are quite consistent to the empirical results from the expected utility model. Using South Africa corn data, we investigate growers' demand and efficiency of alternative hypothetical weather index crop insurance programs. In contrast to previous work that suggests that a single-variable weather index suffices to develop an insurance contract, this study shows that the insured grower achieves a higher utility from multivariate weather indices. The most important single weather index we found in the study area was GDD, and the combination of rainfall and either temperature or GDD outperformed the single variable indices by a large margin. Depending on the growers risk preference, s/he may choose to buy o r offer such insurance for sale if the price is not actuarially fair. The risk protection value of weather-indexed-insurance follows the predictive power of the index on yield in general, though not exactly.