Human interventions in natural systems have resulted in large changes in vegetation composition and distribution patterns.The human induced climate change has added new dimension to such changes.The vegetation types of Northeastern Himalaya are known for highest levels of biodiversity.Conversion due to shifting cultivation, illegal logging and agricultural expansion are major problems that are hampering conservation efforts.Yet, areas vulnerable to climate change are unknown.In this paper, we predicted areas vulnerable to vegetation cover change using multi-temporal remote sensing data (1999 and 2009) and a multi-layer preceptron neural network (MLPNN) with a Markov change model used to predict status of vegetation cover types in 2030, 2050 and 2080.The climate variables precipitation and temperature have been projected for these years and integrated in the vulnerability assessment.