Abstract
The existing Laspeyres index, Paasche's index, and Fisher's index under classical statistics cannot be applied when observations are indeterminate, imprecise, and uncertain. In this paper, the Laspeyres index, Paasche's index, and Fisher's index are introduced to deal with the data having neutrosophy. We present these indexes when indeterminacy is present in the data. To see the aggregate change in the production of rice crops due to climate change under an uncertain environment, data is collected from nine districts of Punjab, Pakistan. From the data and comparative studies, it is concluded that the proposed indexes are more informative, flexible, and suitable to be applied under indeterminate conditions.