The detrimental environmental effects associated with fashion production and consumption are increasingly recognised, and strategies in place. However, these are production-focused, top-down strategies, which do not reach where the impact is highest - the user phase, or where the scope for improvement is utmost - the design phase. A growing body of academic research, and a niche representation of practitioners have responded by developing lifecycle and whole systems approaches. This PhD thesis seeks to expand on and bring this knowledge to the unexplored domain of the highest impact – the fashion industry’s mass-market segment. Trend-forecasting is integral to the fashion design process, and supports the organisation’s commercial endeavours. This thesis explores the potential of trend-forecasting as a positive agent of change for environmental improvement at systemic level in the fashion industry’s mass-market segment. The first empirical study, Stage 1, is diagnostic and exploratory, mapping the interactions that currently exist between trend-forecasting, fashion design and environmental work. The findings and emergent theories formed the basis for a novel methodology compatible with trend-forecasting methods, processes in fashion design, and the inclusive and transformative processes implicit in sustainability. Stage 2 applies this methodology in an experimental study - a series of creative workshops with mixed fashion industry stakeholder groups in the UK and Sweden. Set in 2026, the workshops explore how the underlying proposition “what if fashion and sustainability were compatible or even synergistic?” could affect attitudinal change, and what its generative potential could be. The study shows that a richer knowledge ecology can foster proactive discussions in the realm of sustainability and fashion. It also reveals how a futures perspective and creative approach can unleash the application of fashion professionals’ skills at strategic and systemic levels. The research resulted in recommendations for the application of the new trend-forecasting methodology on a larger scale.