A comparative analysis study of FIR filter implementation reveals that employing various multiplier design strategies can help identify a high-quality response filter from a range of FIR filters. The significance of filters stems from the rapid growth of communication systems in recent times, as they play a crucial role in these systems. Filters are extensively utilized in digital signal processing applications to achieve objectives such as noise reduction, signal amplification, and data compression. Their primary purpose is to enable the recovery of the original signal at the receiver side, allowing for effective communication. Even if the filtered output is relatively small, a strong filtered signal can be sent to an amplifier to restore the original signal. To achieve this, it is essential for the filter to be both efficient and well-designed. Given the increasing number of communication systems, selecting the right filter becomes paramount to ensure optimal performance and maintain the integrity of the transmitted signal. By comparing the implementation stats of various FIR filters and considering different multiplier design strategies, it is possible to identify a high-quality response filter. Such a filter will contribute to the effective functioning of communication systems by enabling noise reduction, signal amplification, and data compression, ultimately leading to successful signal recovery at the receiver end.