In this paper, we present a model-based video bit rate estimation scheme for reducing the bit rate while maintaining a given target quality in many video streaming services limited by network bandwidth, such as IPTV services. Each item of video content can be stored on a video streaming server and delivered with the estimated bit rate using the proposed scheme, which consists of the following two steps: 1) In the first step, the complexity of each intra-frame in a given item of video content is computed as a frame feature to extract a group of candidate frames with a lot of bits. 2) In the second step, the bit rate of the video content is determined by applying statistical analysis and hypothesis testing to that group. The experimental results show that our scheme can reduce the bit rate by up to 78% with negligible degradation of subjective quality, especially with the low-complexity videos commonly used in IPTV services.