Clinical trials have established high temperature treatment of cancer, i.e. a rise of more than 55°C in tissue temperature, as an effective and reliable non-invasive method in the treatment of cancer. Moreover, with the developments in computational techniques and computing capacity, personalized treatment planning (TP) has matured and has become a potent tool for optimizing treatment quality. In the present investigation a framework has been developed to make the treatment planning more accurate and efficient. Tomographic images (CT scan/MRI) of the cancer affected patients have been processed to produce the actual 3-D model of the cancer tumor through Radio Frequency (RF) or microwave (MW) ablation. In this patient specific modelling the entire temperature history of and degree tissue injury have been logged for the entire ablation process through Pennes' bio heat transfer model. Eventually, that will help the clinical practitioner to plan case specific treatment planning. In case of RF ablation, clinical practitioner uses some empirical chart, to decide on ablation voltage and frequency but this new framework will help them to achieve patient specific parameters, a detailed parametric study has been reported. Last but not the least, presently no tool exists that provides patient-specific treatment planning which is even affordable, and accurate enough to be deployed in common clinics. Such a computational tool will play a major role in the quest to establish TP as an effective addition to the thermal treatment of cancer in, the coming years for cheaper, quicker, and safe treatment planning.