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The in-ability of the vast majority of potato farmers in the five sampled LGAs of Plateau state to properly harness the rich climatic condition and get to know when and where to plant or grow, the required quantity and specific seedling to plant and expected yield with date of harvest; were what motivated this study. This article leveraged on the use of remote sensing data, Moderate Resolution Imaging Spectro-Radiometer and Normalized Difference Vegetation Index (MODIS and NDVI) and models from which a timely calendar for potato farmers in the sampled areas were generated. MODIS was used for modeling and predicting potato farming, while the result of NDVI was used to determine the revealed variation in climate, time, temperature, soil moisture content, greenness of land, extent of crop in term of acreage, etc. The single average vegetation index (SAVI) created a scenario whereby a single NDVI data applied on a specified acreage of potato land under investigation in order to make predictions and model for that particular portion. But, the coefficient of normarlized difference vegetation index (CNDVI) allows for comparing correlation coefficient of two or more NDVIs in order to draw inference and predict/model accurately; while coefficient of single average vegetation index (CSAVI) was used to assert if the coefficient of the phenology calendar for a single crop in a specified location, whether it is true or false, and if it is true, then the hypothesis were inferred and applied as such. Subsequently, the result was interpreted into the local languages in order to benefit the vast majority of the local potato farmers that are not literate in English language. This formed a foundation for both the farmers and policy makers to formulate informed decision or policy to harness these inherent potentials.