Bone mineral density (BMD) is a critical clinical indicator of osteoporosis, measured by dual-energy X-ray absorptiometry (DXA). Due to the limited access to DXA machines, osteoporosis is often under-diagnosed and under-treated, leading to an increased risk of fragility fractures. In this work, we present an alternative deep learning-based method for BMD estimation and opportunistic osteoporosis screening using plain film radiography. Our method achieves high performance on three datasets of hip, lumbar spine, and chest radiographs, indicating the strong feasibility of opportunistic osteoporosis screening using plain film radiography.