The evaluation of total and differential settlement plays a pivotal role in geotechnical designs, as excessive settlement leads to serviceability problems. Inorganic clayey soil fails to fulfill the serviceability criteria mainly due to excessive settlement in the form of consolidation settlement. Assessing the extent of consolidation settlement in clayey soil is a highly tedious task. In the proposed study, the Artificial Neural Network was utilized to create a model aimed at predicting consolidation settlements. The input parameters for the proposed study were derived from on-site boring test data, which included uncertain soil parameters such as compression index, preconsolidation pressure and initial void ratio. The estimated results from the neural model were then compared with the probabilistic consolidation settlement, which matched well with the former.