The refractivity profile variation in tropo-sphere is one of the aspects that influ-ences long-distance terrestrial electro-magnetic wave propagation and perfor-mance of communication systems. This study is aimed at calculating and estimat-ing radio refractivity at Makurdi with tropospheric parameters of relative hu-midity, absolute temperature and atmos-pheric pressure using ITU-R and artifi-cial neural network models. Validation results are thus, absolute temperature= 0.4313 K, relative humidity= 0.9989%, pressure= 0.0201 (hpa) respectively. The validation of the correlation coefficient results shows that all the tropospheric pa-rameters have effects on radio re-fractivity, but relative humidity has more effect which is attributed to the large quantity of moisture at the troposphere. From the estimation results, it is clear that artificial neural network has the capacity of estimating tropopheric refractivity since the estimated values has close agreement with the calculated values.