This paper presents the proposal developed for the JUST-NLP 2025 Shared Task on Legal Summarization, which aims to generate abstractive summaries of Indian court judgments. The work describes the motivation, dataset analysis, related work, and proposed methodology based on Large Language Models (LLMs). We analyze the Indian Legal Summarization (InLSum) dataset, review four relevant articles in the summarization of legal texts, and describe the experimental setup involving GPT-4.1 to evaluate the effectiveness of different prompting strategies. The evaluation will follow the ROUGE and BLEU metrics, consistent with the competition protocol.