Church Slavic is a low-resource historical language with limited resources and few experts. We explore the capabilities of off-the-shelf Large Language Models (LLMs) as Church Slavic translators by prompting multiple models in zero-shot and few-shot scenarios. We evaluate four LLMs of varying sizes on 262 sentence pairs translating Church Slavic into English and German, and conduct a second experiment examining the impact of model size using five Qwen2.5-Instruct variants. Our results show that on average EuroLLM-9B-Instruct achieves the best performance, outperforming much larger models. We find minimal benefit from few-shot prompting and performance gaps between English and German as target languages. The automated evaluation metrics suggest that LLMs can produce useful draft translations for Church Slavic, potentially assisting scholars in accessing historical texts.