Optical cameras aboard spacecraft are an essential source of science and engineering data. Testing and development of new and novel spaceborne imaging systems is important in order to facilitate the next generation of space exploration, but can be costly and resource intensive. Image simulation provides a fast and low cost means by which to support development of imaging systems for use in space, and is particularly valuable for supporting proposals, initial concept studies, and projects with limited funding and personnel. Simulated images can be rapidly generated and used to test algorithms (such as autonomous navigation), verify performance requirements (such as signal to noise ratio), and inform design (such as aperture sizing). This paper describes SIMply, an accessible, free, open-source Python image simulation tool developed for simulating spaceborne image data. The tool can be used to simulate physically accurate images of a wide variety of planetary exploration scenes (from planets and moons to small bodies and artificial objects; it is not suitable for extrasolar objects) and is written with an emphasis on simplicity and flexibility to minimize barriers to its use. SIMply utilizes ray tracing and physical models of surface shape, spectral reflectance, spectral camera response, and imaging geometry. SIMply’s physical accuracy is validated and discussed by considering radiometric properties and image features of 4 simulated versions of real spaceborne images, and the importance of input data selection in space image simulation is discussed. The validation approach can be readily adapted and applied to other image simulation tools and scenarios.