Solar variability governs the electromagnetic, radiative, and particulate environment in the heliosphere creating hazardous weather in space through eruptive events such as solar flares, coronal mass ejections. Moreover, modulation in solar output in terms of solar irradiance defines space climate. Both the short and long-term solar variabilities are closely associated with and mostly dominated by the sunspot cycle. Thus, in the context of space weather studies, predicting the sunspot cycle has gained a significant impetus in recent times. However, scientific studies have shown that the intrinsic stochastic nature of the solar convection zone limits the range of predictability to half a solar cycle, and, the dipolar field during the cycle minimum is one of the best precursors for sunspot cycle prediction. In comparison, we have devised a methodology by combining an observational data-driven surface flux transport model and an interior dynamo model to extend the prediction time window to decadal scale. This new methodology has been validated by performing a century-scale data-driven simulation which reproduced the past observation quite successfully — the first of its kind. Subsequently, we employ this technique for predicting sunspot cycle 25 while considering various possible uncertainties. Our ensemble forecast indicates cycle 25 would be similar or slightly stronger than the current cycle and peak around 2024. Sunspot cycle 25 may thus reverse the persistent weakening trend in solar activity which has led to speculation of an imminent Maunder-like grand minimum and cooling of global climate.