Simulations have become remarkably useful in evaluating the performance of new techniques and algorithms in communication networks. This is due to its comparative cost, time and complexity advantage over the analytical and field trial approaches. For large-scale networks, system-level simulators (SLS) are used to assess the performance of the systems. The SLS typically employs statistical channel models to characterize the propagation environment. However, the communication channels can be more accurately modeled using the deterministic ray tracing tools, though at the cost of higher complexity. In this work, we present a novel framework for a hybrid system that integrates both the ray tracer and the SLS. In the hybrid system, the channel strength in terms of the signal-to-noise ratio (SNR) is fed from the ray tracer to the SLS which then uses the values for further tasks such as resource allocation and the consequent performance evaluation. Using metrics such as user throughput and spectral efficiency, our results show that the hybrid system predicts the system performance more accurately than the baseline SLS without ray tracing. The hybrid system will thus facilitate the accurate assessment of the performance of next-generation wireless systems.