This study presents the Artificial Neural Network (ANN) modeling of coiling temperature (CT) for the dual-phase (DP) steel in hot strip mill (HSM) of Tata Steel. CT is highly affecting the final mechanical properties of steel, so it is one of the important parameters in the production of DP steel and hence its modeling becomes important. Even there found lack of CT model in literature, and due to all these reasons, present modeling work is undertaken. The new CT model developed using ANN for HSM by considering critical parameters at run out table which are directly responsible for the variation of CT value. Developed CT model found reliable with correlation coefficient value of 88.4%. Finally, the CT model is validated with actual measured CT for DP steel which was not considered for modeling and it was found that CT model is affirming well with the actual CT pattern for the considered DP steel.